Lars Schmidt-Thieme

322 papers A* 24A 24B 37C 6Misc 8Journal 102Unranked 110

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	HPMixer: Hierarchical Patching for Multivariate Time Series Forecasting. CoRR Jung Min Choi, Vijaya Krishna Yalavarthi, Lars Schmidt-Thieme
2026	J	`jnl`	HexFormer: Hyperbolic Vision Transformer with Exponential Map Aggregation. CoRR Haya Alyoussef, Ahmad Bdeir, Diego Coello de Portugal Mecke, Tom Hanika, Niels Landwehr, Lars Schmidt-Thieme
2026	J	`jnl`	LAtte: Hyperbolic Lorentz Attention for Cross-Subject EEG Classification. CoRR Johannes Burchert, Ahmad Bdeir, Tom Hanika, Lars Schmidt-Thieme, Niels Landwehr
2025	J	`jnl`	An inter- and intra-attention model for multi-behavior recommendation. Int. J. Data Sci. Anal. Shereen Elsayed, Ahmed Rashed, Lars Schmidt-Thieme
2025	—	`conf`	Attribute and Context-Aware Multi-Behavior Model for Unique-Item Recommendation. ECML/PKDD (9) Shereen Elsayed, Ngoc Son Le, Ahmed Rashed, Lars Schmidt-Thieme
2025	—	`conf`	Attribute-Aware Sequential Recommendation Model for Used Car Auctions. ECML/PKDD (9) Shereen Elsayed, Ngoc Son Le, Ahmed Rashed, Lukas Hestermeyer, Radoslaw Wlodarczyk, Maximilian Stubbemann, Lars Schmidt-Thieme
2025	J	`jnl`	Bayesian Active Learning By Distribution Disagreement. CoRR Thorben Werner, Lars Schmidt-Thieme
2025	J	`jnl`	Channel Dependence, Limited Lookback Windows, and the Simplicity of Datasets: How Biased is Time Series Forecasting? CoRR Ibram Abdelmalak, Kiran Madhusudhanan, Jungmin Choi, Maximilian Stubbemann, Lars Schmidt-Thieme
2025	J	`jnl`	IMTS-Mixer: Mixer-Networks for Irregular Multivariate Time Series Forecasting. CoRR Christian Klötergens, Tim Dernedde, Lars Schmidt-Thieme
2025	—	`conf`	Moco: A Learnable Meta Optimizer for Combinatorial Optimization. PAKDD (3) Tim Dernedde, Daniela Thyssens, Sören Dittrich, Maximilian Stubbemann, Lars Schmidt-Thieme
2025	A*	`conf`	Motif-aware Graph Neural Networks for Networked Time Series Imputation. AAAI Nourhan Ahmed, Vijaya Krishna Yalavarthi, Lars Schmidt-Thieme
2025	J	`jnl`	On Distributional Dependent Performance of Classical and Neural Routing Solvers. CoRR Daniela Thyssens, Tim Dernedde, Wilson Sentanoe, Lars Schmidt-Thieme
2025	J	`jnl`	Physiome-ODE: A Benchmark for Irregularly Sampled Multivariate Time Series Forecasting Based on Biological ODEs. CoRR Christian Klötergens, Vijaya Krishna Yalavarthi, Randolf Scholz, Maximilian Stubbemann, Stefan Born, Lars Schmidt-Thieme
2025	A*	`conf`	Physiome-ODE: A Benchmark for Irregularly Sampled Multivariate Time-Series Forecasting Based on Biological ODEs. ICLR Christian Klötergens, Vijaya Krishna Yalavarthi, Randolf Scholz, Maximilian Stubbemann, Stefan Born, Lars Schmidt-Thieme
2025	A*	`conf`	Probabilistic Forecasting of Irregularly Sampled Time Series with Missing Values via Conditional Normalizing Flows. AAAI Vijaya Krishna Yalavarthi, Randolf Scholz, Stefan Born, Lars Schmidt-Thieme
2025	J	`jnl`	Recurrent State Encoders for Efficient Neural Combinatorial Optimization. CoRR Tim Dernedde, Daniela Thyssens, Lars Schmidt-Thieme
2025	J	`jnl`	STADE: Standard Deviation as a Pruning Metric. CoRR Diego Coello de Portugal Mecke, Haya Alyoussef, Ilia Koloiarov, Maximilian Stubbemann, Lars Schmidt-Thieme
2025	A	`conf`	TabResFlow: A Normalizing Spline Flow Model for Probabilistic Univariate Tabular Regression. ECAI Kiran Madhusudhanan, Vijaya Krishna Yalavarthi, Jonas Sonntag, Maximilian Stubbemann, Lars Schmidt-Thieme
2025	J	`jnl`	TabResFlow: A Normalizing Spline Flow Model for Probabilistic Univariate Tabular Regression. CoRR Kiran Madhusudhanan, Vijaya Krishna Yalavarthi, Jonas Sonntag, Maximilian Stubbemann, Lars Schmidt-Thieme
2025	J	`jnl`	The Role of Active Learning in Modern Machine Learning. CoRR Thorben Werner, Lars Schmidt-Thieme, Vijaya Krishna Yalavarthi
2024	A*	`conf`	A Cross-Domain Benchmark for Active Learning. NeurIPS Thorben Werner, Johannes Burchert, Maximilian Stubbemann, Lars Schmidt-Thieme
2024	J	`jnl`	A Cross-Domain Benchmark for Active Learning. CoRR Thorben Werner, Johannes Burchert, Maximilian Stubbemann, Lars Schmidt-Thieme
2024	J	`jnl`	Are EEG Sequences Time Series? EEG Classification with Time Series Models and Joint Subject Training. CoRR Johannes Burchert, Thorben Werner, Vijaya Krishna Yalavarthi, Diego Coello de Portugal, Maximilian Stubbemann, Lars Schmidt-Thieme
2024	—	`conf`	Functional Latent Dynamics for Irregularly Sampled Time Series Forecasting. ECML/PKDD (4) Christian Klötergens, Vijaya Krishna Yalavarthi, Maximilian Stubbemann, Lars Schmidt-Thieme
2024	J	`jnl`	Functional Latent Dynamics for Irregularly Sampled Time Series Forecasting. CoRR Christian Klötergens, Vijaya Krishna Yalavarthi, Maximilian Stubbemann, Lars Schmidt-Thieme
2024	A*	`conf`	GraFITi: Graphs for Forecasting Irregularly Sampled Time Series. AAAI Vijaya Krishna Yalavarthi, Kiran Madhusudhanan, Randolf Scholz, Nourhan Ahmed, Johannes Burchert, Shayan Jawed, Stefan Born, Lars Schmidt-Thieme
2024	J	`jnl`	HMAR: Hierarchical Masked Attention for Multi-Behaviour Recommendation. CoRR Shereen Elsayed, Ahmed Rashed, Lars Schmidt-Thieme
2024	—	`conf`	HMAR: Hierarchical Masked Attention for Multi-behaviour Recommendation. PAKDD (5) Shereen Elsayed, Ahmed Rashed, Lars Schmidt-Thieme
2024	—	`conf`	Hyperparameter Tuning MLP's for Probabilistic Time Series Forecasting. PAKDD (6) Kiran Madhusudhanan, Shayan Jawed, Lars Schmidt-Thieme
2024	J	`jnl`	Hyperparameter Tuning MLPs for Probabilistic Time Series Forecasting. CoRR Kiran Madhusudhanan, Shayan Jawed, Lars Schmidt-Thieme
2024	—	`conf`	Learning Set Embeddings for Fashion Compatibility Recommendation. SURE@RecSys Indra Firmansyah, Randolf Scholz, Adrian Nahmendorff, Ngoc Son Le, Shereen Elsayed, Lars Schmidt-Thieme
2024	J	`jnl`	Learning attentive attribute-aware node embeddings in dynamic environments. Int. J. Data Sci. Anal. Nourhan Ahmed, Ahmed Rashed, Lars Schmidt-Thieme
2024	J	`jnl`	Marginalization Consistent Mixture of Separable Flows for Probabilistic Irregular Time Series Forecasting. CoRR Vijaya Krishna Yalavarthi, Randolf Scholz, Kiran Madhusudhanan, Stefan Born, Lars Schmidt-Thieme
2024	J	`jnl`	Moco: A Learnable Meta Optimizer for Combinatorial Optimization. CoRR Tim Dernedde, Daniela Thyssens, Sören Dittrich, Maximilian Stubbemann, Lars Schmidt-Thieme
2024	A	`conf`	Multi-Behavioral Sequential Recommendation. RecSys Shereen Elsayed, Ahmed Rashed, Lars Schmidt-Thieme
2024	B	`conf`	ProbSAINT: Probabilistic Tabular Regression for Used Car Pricing. IEEE Big Data Kiran Madhusudhanan, Gunnar Behrens, Maximilian Stubbemann, Lars Schmidt-Thieme
2024	J	`jnl`	ProbSAINT: Probabilistic Tabular Regression for Used Car Pricing. CoRR Kiran Madhusudhanan, Gunnar Behrens, Maximilian Stubbemann, Lars Schmidt-Thieme
2024	J	`jnl`	Probabilistic Forecasting of Irregular Time Series via Conditional Flows. CoRR Vijaya Krishna Yalavarthi, Randolf Scholz, Stefan Born, Lars Schmidt-Thieme
2024	J	`jnl`	Structure-aware decoupled imputation network for multivariate time series. Data Min. Knowl. Discov. Nourhan Ahmed, Lars Schmidt-Thieme
2023	J	`jnl`	Context-Aware Sequential Model for Multi-Behaviour Recommendation. CoRR Shereen Elsayed, Ahmed Rashed, Lars Schmidt-Thieme
2023	—	`conf`	ConvMix: Combining Intermediate Latent Features in Deep Convolutional Neural Networks. SCIA (2) Mofassir ul Islam Arif, Johannes Burchert, Lars Schmidt-Thieme
2023	B	`conf`	Deep Multi-Representation Model for Click-Through Rate Prediction. IJCNN Shereen Elsayed, Lars Schmidt-Thieme
2023	—	`conf`	DeepStay: Stay Region Extraction from Location Trajectories Using Weak Supervision. ITSC Christian Löwens, Daniela Thyssens, Emma Andersson, Christina Jenkins, Lars Schmidt-Thieme
2023	J	`jnl`	DeepStay: Stay Region Extraction from Location Trajectories using Weak Supervision. CoRR Christian Löwens, Daniela Thyssens, Emma Andersson, Christina Jenkins, Lars Schmidt-Thieme
2023	J	`jnl`	Directly Optimizing IoU for Bounding Box Localization. CoRR Mofassir ul Islam Arif, Mohsan Jameel, Lars Schmidt-Thieme
2023	—	`conf`	Few-Shot Human Motion Prediction for Heterogeneous Sensors. PAKDD (2) Rafael Rêgo Drumond, Lukas Brinkmeyer, Lars Schmidt-Thieme
2023	B	`conf`	Forecasting Early with Meta Learning. IJCNN Shayan Jawed, Kiran Madhusudhanan, Vijaya Krishna Yalavarthi, Lars Schmidt-Thieme
2023	J	`jnl`	Forecasting Early with Meta Learning. CoRR Shayan Jawed, Kiran Madhusudhanan, Vijaya Krishna Yalavarthi, Lars Schmidt-Thieme
2023	J	`jnl`	Forecasting Irregularly Sampled Time Series using Graphs. CoRR Vijaya Krishna Yalavarthi, Kiran Madusudanan, Randolf Scholz, Nourhan Ahmed, Johannes Burchert, Shayan Jawed, Stefan Born, Lars Schmidt-Thieme
2023	A*	`conf`	Neural Capacitated Clustering. IJCAI Jonas K. Falkner, Lars Schmidt-Thieme
2023	J	`jnl`	Neural Capacitated Clustering. CoRR Jonas K. Falkner, Lars Schmidt-Thieme
2023	J	`jnl`	Phantom Embeddings: Using Embedding Space for Model Regularization in Deep Neural Networks. CoRR Mofassir ul Islam Arif, Mohsan Jameel, Josif Grabocka, Lars Schmidt-Thieme
2023	B	`conf`	Pricing Used Vehicles at Volkswagen Financial Services AG. IEEE Big Data Shayan Jawed, Jan Stening, Lars Schmidt-Thieme
2023	J	`jnl`	Routing Arena: A Benchmark Suite for Neural Routing Solvers. CoRR Daniela Thyssens, Tim Dernedde, Jonas K. Falkner, Lars Schmidt-Thieme
2023	B	`conf`	Sparse Self-Attention Guided Generative Adversarial Networks for Time-Series Generation. DSAA Nourhan Ahmed, Lars Schmidt-Thieme
2023	J	`jnl`	Sparse self-attention guided generative adversarial networks for time-series generation. Int. J. Data Sci. Anal. Nourhan Ahmed, Lars Schmidt-Thieme
2023	J	`jnl`	Too Big, so Fail? - Enabling Neural Construction Methods to Solve Large-Scale Routing Problems. CoRR Jonas K. Falkner, Lars Schmidt-Thieme
2023	B	`conf`	Tripletformer for Probabilistic Interpolation of Irregularly sampled Time Series. IEEE Big Data Vijaya Krishna Yalavarthi, Johannes Burchert, Lars Schmidt-Thieme
2022	J	`jnl`	A.I. and Data-Driven Mobility at Volkswagen Financial Services AG. CoRR Shayan Jawed, Mofassir ul Islam Arif, Ahmed Rashed, Kiran Madhusudhanan, Shereen Elsayed, Mohsan Jameel, Alexei Volk, Andre Hintsches, Marlies Kornfeld, Katrin Lange, Lars Schmidt-Thieme
2022	J	`jnl`	Attention, Filling in The Gaps for Generalization in Routing Problems. CoRR Ahmad Bdeir, Jonas K. Falkner, Lars Schmidt-Thieme
2022	—	`conf`	Attention, Filling in the Gaps for Generalization in Routing Problems. ECML/PKDD (6) Ahmad Bdeir, Jonas K. Falkner, Lars Schmidt-Thieme
2022	J	`jnl`	Auxiliary Quantile Forecasting with Linear Networks. CoRR Shayan Jawed, Lars Schmidt-Thieme
2022	J	`jnl`	CARCA: Context and Attribute-Aware Next-Item Recommendation via Cross-Attention. CoRR Ahmed Rashed, Shereen Elsayed, Lars Schmidt-Thieme
2022	A	`conf`	Context and Attribute-Aware Sequential Recommendation via Cross-Attention. RecSys Ahmed Rashed, Shereen Elsayed, Lars Schmidt-Thieme
2022	B	`conf`	DCSF: Deep Convolutional Set Functions for Classification of Asynchronous Time Series. DSAA Vijaya Krishna Yalavarthi, Johannes Burchert, Lars Schmidt-Thieme
2022	J	`jnl`	DCSF: Deep Convolutional Set Functions for Classification of Asynchronous Time Series. CoRR Vijaya Krishna Yalavarthi, Johannes Burchert, Lars Schmidt-Thieme
2022	—	`conf`	Deep Level Annotation for Painter Attribution on Greek Vases utilizing Object Detection. SUMAC @ ACM Multimedia Marta Kipke, Lukas Brinkmeyer, Souaybou Bagayoko, Lars Schmidt-Thieme, Martin Langner
2022	J	`jnl`	Deep Multi-Representation Model for Click-Through Rate Prediction. CoRR Shereen Elsayed, Lars Schmidt-Thieme
2022	—	`conf`	Does Self-Supervised Pretraining Really Match ImageNet Weights? IVMSP Daniel Pototzky, Azhar Sultan, Lars Schmidt-Thieme
2022	J	`jnl`	End-to-End Image-Based Fashion Recommendation. CoRR Shereen Elsayed, Lukas Brinkmeyer, Lars Schmidt-Thieme
2022	—	`conf`	FastSiam: Resource-Efficient Self-supervised Learning on a Single GPU. GCPR Daniel Pototzky, Azhar Sultan, Lars Schmidt-Thieme
2022	—	`conf`	Few-Shot Forecasting of Time-Series with Heterogeneous Channels. ECML/PKDD (6) Lukas Brinkmeyer, Rafael Rêgo Drumond, Johannes Burchert, Lars Schmidt-Thieme
2022	J	`jnl`	Few-Shot Forecasting of Time-Series with Heterogeneous Channels. CoRR Lukas Brinkmeyer, Rafael Rêgo Drumond, Johannes Burchert, Lars Schmidt-Thieme
2022	J	`jnl`	Few-shot human motion prediction for heterogeneous sensors. CoRR Rafael Rêgo Drumond, Lukas Brinkmeyer, Lars Schmidt-Thieme
2022	B	`conf`	GQFormer: A Multi-Quantile Generative Transformer for Time Series Forecasting. IEEE Big Data Shayan Jawed, Lars Schmidt-Thieme
2022	J	`jnl`	Improving Amharic Handwritten Word Recognition Using Auxiliary Task. CoRR Mesay Samuel Gondere, Lars Schmidt-Thieme, Durga Prasad Sharma, Abiot Sinamo Boltena
2022	J	`jnl`	Large Neighborhood Search based on Neural Construction Heuristics. CoRR Jonas K. Falkner, Daniela Thyssens, Lars Schmidt-Thieme
2022	—	`conf`	Learning to Control Local Search for Combinatorial Optimization. ECML/PKDD (5) Jonas K. Falkner, Daniela Thyssens, Ahmad Bdeir, Lars Schmidt-Thieme
2022	J	`jnl`	Learning to Control Local Search for Combinatorial Optimization. CoRR Jonas K. Falkner, Daniela Thyssens, Ahmad Bdeir, Lars Schmidt-Thieme
2022	—	`conf`	Offline Handwritten Amharic Character Recognition Using Few-Shot Learning. PanAfriCon AI Mesay Samuel Samuel, Lars Schmidt-Thieme, Durga Prasad Sharma, Abiot Sinamo Boltena, Abey Bruck
2022	J	`jnl`	Offline Handwritten Amharic Character Recognition Using Few-shot Learning. CoRR Mesay Samuel Gondere, Lars Schmidt-Thieme, Durga Prasad Sharma, Abiot Sinamo Boltena, Abey Bruck
2022	B	`conf`	On the Potential of Using ERP Business and System Data for Fraud Detection. IEEE Big Data Jonas Schnepf, Paula Vetter, Tarik Temel, Bernd Scheuermann, Lars Schmidt-Thieme
2022	—	`conf`	Open Set Recognition for Time Series Classification. PAKDD (2) Tolga Akar, Thorben Werner, Vijaya Krishna Yalavarthi, Lars Schmidt-Thieme
2022	—	`conf`	Parting With Illusions About Synthetic Data. IVMSP Daniel Pototzky, Azhar Sultan, Lars Schmidt-Thieme
2022	B	`conf`	Positive-Unlabeled Domain Adaptation. DSAA Jonas Sonntag, Gunnar Behrens, Lars Schmidt-Thieme
2022	J	`jnl`	Positive-Unlabeled Domain Adaptation. CoRR Jonas Sonntag, Gunnar Behrens, Lars Schmidt-Thieme
2022	J	`jnl`	Put Attention to Temporal Saliency Patterns of Multi-Horizon Time Series. CoRR Nghia Duong-Trung, Stefan Born, Kiran Madhusudhanan, Randolf Scholz, Johannes Burchert, Danh Le Phuoc, Lars Schmidt-Thieme
2022	Misc	`conf`	Solving the Traveling Salesperson Problem with Precedence Constraints by Deep Reinforcement Learning. KI Christian Löwens, Inaam Ashraf, Alexander Gembus, Genesis Cuizon, Jonas K. Falkner, Lars Schmidt-Thieme
2022	J	`jnl`	Solving the Traveling Salesperson Problem with Precedence Constraints by Deep Reinforcement Learning. CoRR Christian Löwens, Inaam Ashraf, Alexander Gembus, Genesis Cuizon, Jonas K. Falkner, Lars Schmidt-Thieme
2022	J	`jnl`	Supervised Permutation Invariant Networks for Solving the CVRP with Bounded Fleet Size. CoRR Daniela Thyssens, Jonas K. Falkner, Lars Schmidt-Thieme
2022	J	`jnl`	Tripletformer for Probabilistic Interpolation of Asynchronous Time Series. CoRR Vijaya Krishna Yalavarthi, Johannes Burchert, Lars Schmidt-Thieme
2022	—	`conf`	U-Net Inspired Transformer Architecture for Far Horizon Time Series Forecasting. ECML/PKDD (6) Kiran Madhusudhanan, Johannes Burchert, Nghia Duong-Trung, Stefan Born, Lars Schmidt-Thieme
2022	J	`jnl`	When Bioprocess Engineering Meets Machine Learning: A Survey from the Perspective of Automated Bioprocess Development. CoRR Nghia Duong-Trung, Stefan Born, Jong Woo Kim, Marie-Therese Schermeyer, Katharina Paulick, Maxim Borisyak, Ernesto C. Martínez, Mariano Nicolás Cruz Bournazou, Thorben Werner, Randolf Scholz, Lars Schmidt-Thieme, Peter Neubauer
2022	J	`jnl`	Zero-Shot AutoML with Pretrained Models. CoRR Ekrem Öztürk, Fabio Ferreira, Hadi S. Jomaa, Lars Schmidt-Thieme, Josif Grabocka, Frank Hutter
2022	A*	`conf`	Zero-shot AutoML with Pretrained Models. ICML Ekrem Öztürk, Fabio Ferreira, Hadi S. Jomaa, Lars Schmidt-Thieme, Josif Grabocka, Frank Hutter
2021	A*	`conf`	A Guided Learning Approach for Item Recommendation via Surrogate Loss Learning. SIGIR Ahmed Rashed, Josif Grabocka, Lars Schmidt-Thieme
2021	J	`jnl`	Dataset2Vec: learning dataset meta-features. Data Min. Knowl. Discov. Hadi S. Jomaa, Lars Schmidt-Thieme, Josif Grabocka
2021	J	`jnl`	Deep Metric Learning for Ground Images. CoRR Raaghav Radhakrishnan, Jan Fabian Schmid, Randolf Scholz, Lars Schmidt-Thieme
2021	J	`jnl`	Do We Really Need Deep Learning Models for Time Series Forecasting? CoRR Shereen Elsayed, Daniela Thyssens, Ahmed Rashed, Lars Schmidt-Thieme, Hadi Samer Jomaa
2021	J	`jnl`	Hyperparameter Optimization with Differentiable Metafeatures. CoRR Hadi S. Jomaa, Lars Schmidt-Thieme, Josif Grabocka
2021	J	`jnl`	Improving Hyperparameter Optimization by Planning Ahead. CoRR Hadi S. Jomaa, Jonas K. Falkner, Lars Schmidt-Thieme
2021	—	`conf`	Leveraging Group Annotations in Object Detection Using Graph-Based Pseudo-labeling. GCPR Daniel Pototzky, Matthias Kirschner, Lars Schmidt-Thieme
2021	J	`jnl`	Multi-script Handwritten Digit Recognition Using Multi-task Learning. CoRR Mesay Samuel Gondere, Lars Schmidt-Thieme, Durga Prasad Sharma, Randolf Scholz
2021	—	`conf`	Multi-task Learning Curve Forecasting Across Hyperparameter Configurations and Datasets. ECML/PKDD (1) Shayan Jawed, Hadi S. Jomaa, Lars Schmidt-Thieme, Josif Grabocka
2021	—	`conf`	Multimodal Meta-Learning for Time Series Regression. AALTD@ECML/PKDD Sebastian Pineda-Arango, Felix Heinrich, Kiran Madhusudhanan, Lars Schmidt-Thieme
2021	J	`jnl`	Multimodal Meta-Learning for Time Series Regression. CoRR Sebastian Pineda-Arango, Felix Heinrich, Kiran Madhusudhanan, Lars Schmidt-Thieme
2021	A*	`conf`	Predicting Parking Availability from Mobile Payment Transactions with Positive Unlabeled Learning. AAAI Jonas Sonntag, Michael Engel, Lars Schmidt-Thieme
2021	Misc	`conf`	RP-DQN: An Application of Q-Learning to Vehicle Routing Problems. KI Ahmad Bdeir, Simon Boeder, Tim Dernedde, Kirill Tkachuk, Jonas K. Falkner, Lars Schmidt-Thieme
2021	J	`jnl`	RP-DQN: An application of Q-Learning to Vehicle Routing Problems. CoRR Ahmad Bdeir, Simon Boeder, Tim Dernedde, Kirill Tkachuk, Jonas K. Falkner, Lars Schmidt-Thieme
2021	—	`conf`	Self-supervised Learning for Object Detection in Autonomous Driving. GCPR Daniel Pototzky, Azhar Sultan, Matthias Kirschner, Lars Schmidt-Thieme
2021	A	`conf`	Training Object Detectors if Only Large Objects are Labeled. BMVC Daniel Pototzky, Matthias Kirschner, Azhar Sultan, Lars Schmidt-Thieme
2021	J	`jnl`	Yformer: U-Net Inspired Transformer Architecture for Far Horizon Time Series Forecasting. CoRR Kiran Madhusudhanan, Johannes Burchert, Nghia Duong-Trung, Stefan Born, Lars Schmidt-Thieme
2020	—	`conf`	A machine learning approach to infer on-street parking occupancy based on parking meter transactions. ITSC Jonas Sonntag, Lars Schmidt-Thieme
2020	—	`conf`	An efficient evolutionary solution to the joint order batching - order picking planning problem. GECCO Companion Riccardo Lucato, Jonas K. Falkner, Lars Schmidt-Thieme
2020	—	`conf`	Automation of Leasing Vehicle Return Assessment Using Deep Learning Models. ECML/PKDD (4) Mohsan Jameel, Mofassir ul Islam Arif, Andre Hintsches, Lars Schmidt-Thieme
2020	A	`conf`	HIDRA: Head Initialization across Dynamic targets for Robust Architectures. SDM Rafael Rêgo Drumond, Lukas Brinkmeyer, Josif Grabocka, Lars Schmidt-Thieme
2020	J	`jnl`	Learning to Solve Vehicle Routing Problems with Time Windows through Joint Attention. CoRR Jonas K. Falkner, Lars Schmidt-Thieme
2020	A	`conf`	MultiRec: A Multi-Relational Approach for Unique Item Recommendation in Auction Systems. RecSys Ahmed Rashed, Shayan Jawed, Lars Schmidt-Thieme, Andre Hintsches
2020	—	`conf`	Optimal Topology Search for Fast Model Averaging in Decentralized Parallel SGD. PAKDD (2) Mohsan Jameel, Shayan Jawed, Lars Schmidt-Thieme
2020	—	`conf`	Phantom Embeddings: Using Embeddings Space for Model Regularization in Deep Neural Networks. LWDA Mofassir ul Islam Arif, Mohsan Jameel, Josif Grabocka, Lars Schmidt-Thieme
2020	—	`conf`	Self-supervised Learning for Semi-supervised Time Series Classification. PAKDD (1) Shayan Jawed, Josif Grabocka, Lars Schmidt-Thieme
2019	—	`conf`	A Deep Multi-task Approach for Residual Value Forecasting. ECML/PKDD (3) Ahmed Rashed, Shayan Jawed, Jens Rehberg, Josif Grabocka, Lars Schmidt-Thieme, Andre Hintsches
2019	B	`conf`	A Hybrid Convolutional Approach for Parking Availability Prediction. IJCNN Hadi Samer Jomaa, Josif Grabocka, Lars Schmidt-Thieme, Alexander Borek
2019	A	`conf`	Attribute-aware non-linear co-embeddings of graph features. RecSys Ahmed Rashed, Josif Grabocka, Lars Schmidt-Thieme
2019	J	`jnl`	Chameleon: Learning Model Initializations Across Tasks With Different Schemas. CoRR Lukas Brinkmeyer, Rafael Rêgo Drumond, Randolf Scholz, Josif Grabocka, Lars Schmidt-Thieme
2019	J	`jnl`	Data-Driven Vehicle Trajectory Forecasting. CoRR Shayan Jawed, Eya Boumaiza, Josif Grabocka, Lars Schmidt-Thieme
2019	J	`jnl`	Dataset2Vec: Learning Dataset Meta-Features. CoRR Hadi S. Jomaa, Josif Grabocka, Lars Schmidt-Thieme
2019	—	`conf`	Directly Optimizing IoU for Bounding Box Localization. ACPR (1) Mofassir ul Islam Arif, Mohsan Jameel, Lars Schmidt-Thieme
2019	—	`conf`	Gait Verification using Deep Learning with a Pairwise Loss. BIOSIG Vijaya Krishna Yalavarthi, Josif Grabocka, Hareesh Mandalapu, Lars Schmidt-Thieme
2019	J	`jnl`	HIDRA: Head Initialization across Dynamic targets for Robust Architectures. CoRR Rafael Rêgo Drumond, Lukas Brinkmeyer, Josif Grabocka, Lars Schmidt-Thieme
2019	J	`jnl`	Handwritten Amharic Character Recognition Using a Convolutional Neural Network. CoRR Mesay Samuel Gondere, Lars Schmidt-Thieme, Abiot Sinamo Boltena, Hadi Samer Jomaa
2019	J	`jnl`	Hyp-RL : Hyperparameter Optimization by Reinforcement Learning. CoRR Hadi S. Jomaa, Josif Grabocka, Lars Schmidt-Thieme
2019	J	`jnl`	In Hindsight: A Smooth Reward for Steady Exploration. CoRR Hadi S. Jomaa, Josif Grabocka, Lars Schmidt-Thieme
2019	J	`jnl`	Learning Surrogate Losses. CoRR Josif Grabocka, Randolf Scholz, Lars Schmidt-Thieme
2019	—	`conf`	Multi-Label Network Classification via Weighted Personalized Factorizations. ICAART (2) Ahmed Rashed, Josif Grabocka, Lars Schmidt-Thieme
2019	J	`jnl`	Multi-Label Network Classification via Weighted Personalized Factorizations. CoRR Ahmed Rashed, Josif Grabocka, Lars Schmidt-Thieme
2019	A*	`conf`	Multi-Relational Classification via Bayesian Ranked Non-Linear Embeddings. KDD Ahmed Rashed, Josif Grabocka, Lars Schmidt-Thieme
2019	—	`conf`	Multi-step Forecasting via Multi-task Learning. IEEE BigData Shayan Jawed, Ahmed Rashed, Lars Schmidt-Thieme
2019	—	`conf`	Ring-Star: A Sparse Topology for Faster Model Averaging in Decentralized Parallel SGD. PKDD/ECML Workshops (1) Mohsan Jameel, Josif Grabocka, Mofassir ul Islam Arif, Lars Schmidt-Thieme
2019	—	`conf`	Weighted Personalized Factorizations for Network Classification with Approximated Relation Weights. ICAART (Revised Selected Papers) Ahmed Rashed, Josif Grabocka, Lars Schmidt-Thieme
2018	J	`jnl`	NeuralWarp: Time-Series Similarity with Warping Networks. CoRR Josif Grabocka, Lars Schmidt-Thieme
2018	J	`jnl`	Scalable Gaussian process-based transfer surrogates for hyperparameter optimization. Mach. Learn. Martin Wistuba, Nicolas Schilling, Lars Schmidt-Thieme
2018	A*	`conf`	Towards Distributed Pairwise Ranking using Implicit Feedback. SIGIR Mohsan Jameel, Nicolas Schilling, Lars Schmidt-Thieme
2017	A	`conf`	Automatic Frankensteining: Creating Complex Ensembles Autonomously. SDM Martin Wistuba, Nicolas Schilling, Lars Schmidt-Thieme
2017	J	`jnl`	Channel masking for multivariate time series shapelets. CoRR Dripta S. Raychaudhuri, Josif Grabocka, Lars Schmidt-Thieme
2017	J	`jnl`	Collaborative SVM classification in scale-free peer-to-peer networks. Expert Syst. Appl. Muhammad Umer Khan, Lars Schmidt-Thieme, Alexandros Nanopoulos
2017	—	`conf`	Finding Hierarchy of Topics from Twitter Data. LWDA Nghia Duong-Trung, Nicolas Schilling, Lars Schmidt-Thieme
2017	A	`conf`	On Discovering the Number of Document Topics via Conceptual Latent Space. CIKM Nghia Duong-Trung, Lars Schmidt-Thieme
2017	—	`conf`	Personalized Deep Learning for Tag Recommendation. PAKDD (1) Hanh T. H. Nguyen, Martin Wistuba, Josif Grabocka, Lucas Rêgo Drumond, Lars Schmidt-Thieme
2017	—	`conf`	Personalized Tag Recommendation for Images Using Deep Transfer Learning. ECML/PKDD (2) Hanh T. H. Nguyen, Martin Wistuba, Lars Schmidt-Thieme
2016	J	`jnl`	Bank Card Usage Prediction Exploiting Geolocation Information. CoRR Martin Wistuba, Nghia Duong-Trung, Nicolas Schilling, Lars Schmidt-Thieme
2016	J	`jnl`	Fast classification of univariate and multivariate time series through shapelet discovery. Knowl. Inf. Syst. Josif Grabocka, Martin Wistuba, Lars Schmidt-Thieme
2016	—	`conf`	Hybrid Matrix Factorization Update for Progress Modeling in Intelligent Tutoring Systems. CSEDU (Selected Papers) Carlotta Schatten, Lars Schmidt-Thieme
2016	B	`conf`	Hyperparameter Optimization Machines. DSAA Martin Wistuba, Nicolas Schilling, Lars Schmidt-Thieme
2016	B	`conf`	Integrating Distributional and Lexical Information for Semantic Classification of Words using MRMF. COLING Rosa Tsegaye Aga, Lucas Drumond, Christian Wartena, Lars Schmidt-Thieme
2016	J	`jnl`	Latent Time-Series Motifs. ACM Trans. Knowl. Discov. Data Josif Grabocka, Nicolas Schilling, Lars Schmidt-Thieme
2016	—	`conf`	Learning DTW-Shapelets for Time-Series Classification. CODS Mit Shah, Josif Grabocka, Nicolas Schilling, Martin Wistuba, Lars Schmidt-Thieme
2016	B	`conf`	Learning Thesaurus Relations from Distributional Features. LREC Rosa Tsegaye Aga, Christian Wartena, Lucas Drumond, Lars Schmidt-Thieme
2016	—	`conf`	Matrix Factorization for Near Real-time Geolocation Prediction in Twitter Stream. LWDA Nghia Duong-Trung, Nicolas Schilling, Lucas Drumond, Lars Schmidt-Thieme
2016	J	`jnl`	Multi-Relational Learning at Scale with ADMM. CoRR Lucas Drumond, Ernesto Diaz-Aviles, Lars Schmidt-Thieme
2016	A	`conf`	Near Real-time Geolocation Prediction in Twitter Streams via Matrix Factorization Based Regression. CIKM Nghia Duong-Trung, Nicolas Schilling, Lars Schmidt-Thieme
2016	J	`jnl`	Perceived Task-Difficulty Recognition from Log-file Information for the Use in Adaptive Intelligent Tutoring Systems. Int. J. Artif. Intell. Educ. Ruth Janning, Carlotta Schatten, Lars Schmidt-Thieme
2016	—	`conf`	Scalable Hyperparameter Optimization with Products of Gaussian Process Experts. ECML/PKDD (1) Nicolas Schilling, Martin Wistuba, Lars Schmidt-Thieme
2016	—	`conf`	Student Progress Modeling with Skills Deficiency Aware Kalman Filters. CSEDU (1) Carlotta Schatten, Lars Schmidt-Thieme
2016	—	`conf`	Two-Stage Transfer Surrogate Model for Automatic Hyperparameter Optimization. ECML/PKDD (1) Martin Wistuba, Nicolas Schilling, Lars Schmidt-Thieme
2015	B	`conf`	A Transfer Learning Approach for Applying Matrix Factorization to Small ITS Datasets. EDM Lydia Voß, Carlotta Schatten, Claudia Mazziotti, Lars Schmidt-Thieme
2015	J	`jnl`	A supervised active learning framework for recommender systems based on decision trees. User Model. User Adapt. Interact. Rasoul Karimi, Alexandros Nanopoulos, Lars Schmidt-Thieme
2015	J	`jnl`	Beyond Manual Tuning of Hyperparameters. Künstliche Intell. Frank Hutter, Jörg Lücke, Lars Schmidt-Thieme
2015	—	`conf`	Comparing Prediction Models for Active Learning in Recommender Systems. LWA Rasoul Karimi, Christoph Freudenthaler, Alexandros Nanopoulos, Lars Schmidt-Thieme
2015	—	`conf`	Geo_ML @ MediaEval Placing Task 2015. MediaEval Nghia Duong-Trung, Martin Wistuba, Lucas Rêgo Drumond, Lars Schmidt-Thieme
2015	B	`conf`	How to Aggregate Multimodal Features for Perceived Task Difficulty Recognition in Intelligent Tutoring Systems. EDM Ruth Janning, Carlotta Schatten, Lars Schmidt-Thieme
2015	—	`conf`	Hyperparameter Optimization with Factorized Multilayer Perceptrons. ECML/PKDD (2) Nicolas Schilling, Martin Wistuba, Lucas Drumond, Lars Schmidt-Thieme
2015	—	`conf`	Hyperparameter Search Space Pruning - A New Component for Sequential Model-Based Hyperparameter Optimization. ECML/PKDD (2) Martin Wistuba, Nicolas Schilling, Lars Schmidt-Thieme
2015	B	`conf`	Improving Automatic Affect Recognition on Low-Level Speech Features in Intelligent Tutoring Systems. EC-TEL Ruth Janning, Carlotta Schatten, Lars Schmidt-Thieme
2015	A*	`conf`	Integration and Evaluation of a Matrix Factorization Sequencer in Large Commercial ITS. AAAI Carlotta Schatten, Ruth Janning, Lars Schmidt-Thieme
2015	B	`conf`	Joint Model Choice and Hyperparameter Optimization with Factorized Multilayer Perceptrons. ICTAI Nicolas Schilling, Martin Wistuba, Lucas Drumond, Lars Schmidt-Thieme
2015	—	`conf`	Learning Data Set Similarities for Hyperparameter Optimization Initializations. MetaSel@PKDD/ECML Martin Wistuba, Nicolas Schilling, Lars Schmidt-Thieme
2015	J	`jnl`	Learning Through Non-linearly Supervised Dimensionality Reduction. Trans. Large Scale Data Knowl. Centered Syst. Josif Grabocka, Lars Schmidt-Thieme
2015	B	`conf`	Learning hyperparameter optimization initializations. DSAA Martin Wistuba, Nicolas Schilling, Lars Schmidt-Thieme
2015	—	`conf`	Multi-relational Factorization Models for Student Modeling in Intelligent Tutoring Systems. KSE Nguyen Thai-Nghe, Lars Schmidt-Thieme
2015	J	`jnl`	Optimal Time-Series Motifs. CoRR Josif Grabocka, Nicolas Schilling, Lars Schmidt-Thieme
2015	—	`conf`	Recognizing Perceived Task Difficulty from Speech and Pause Histograms. EDM (Workshops) Ruth Janning, Carlotta Schatten, Lars Schmidt-Thieme
2015	—	`conf`	Recognizing Perceived Task Difficulty from Speech, Pause Histograms. AIED Workshops Ruth Janning, Carlotta Schatten, Lars Schmidt-Thieme
2015	J	`jnl`	Scalable Classification of Repetitive Time Series Through Frequencies of Local Polynomials. IEEE Trans. Knowl. Data Eng. Josif Grabocka, Martin Wistuba, Lars Schmidt-Thieme
2015	J	`jnl`	Scalable Discovery of Time-Series Shapelets. CoRR Josif Grabocka, Martin Wistuba, Lars Schmidt-Thieme
2015	A*	`conf`	Sequential Model-Free Hyperparameter Tuning. ICDM Martin Wistuba, Nicolas Schilling, Lars Schmidt-Thieme
2015	J	`jnl`	Ultra-Fast Shapelets for Time Series Classification. CoRR Martin Wistuba, Josif Grabocka, Lars Schmidt-Thieme
2014	—	`conf`	Adaptive Content Sequencing without Domain Information. CSEDU (1) Carlotta Schatten, Lars Schmidt-Thieme
2014	B	`conf`	An SVM Plait for Improving Affect Recognition in Intelligent Tutoring Systems. ICTAI Ruth Janning, Carlotta Schatten, Lars Schmidt-Thieme, Gerhard Backfried, Norbert Pfannerer
2014	—	`conf`	Analyzing cooperative lane change models for connected vehicles. ICCVE Muhammad Umer Khan, Pavlos Basaras, Lars Schmidt-Thieme, Alexandros Nanopoulos, Dimitrios Katsaros
2014	C	`conf`	Automatic Subclasses Estimation for a Better Classification with HNNP. ISMIS Ruth Janning, Carlotta Schatten, Lars Schmidt-Thieme
2014	J	`jnl`	Buried pipe localization using an iterative geometric clustering on GPR data. Artif. Intell. Rev. Ruth Janning, André Busche, Tomás Horváth, Lars Schmidt-Thieme
2014	—	`conf`	Collective Matrix Factorization of Predictors, Neighborhood and Targets for Semi-supervised Classification. PAKDD (1) Lucas Rêgo Drumond, Lars Schmidt-Thieme, Christoph Freudenthaler, Artus Krohn-Grimberghe
2014	—	`ed.`	Data Analysis, Machine Learning and Knowledge Discovery - Proceedings of the 36th Annual Conference of the Gesellschaft für Klassifikation e. V., Hildesheim, Germany, August 2012. GfKl Myra Spiliopoulou, Lars Schmidt-Thieme, Ruth Janning
2014	B	`conf`	Feature Analysis for Affect Recognition Supporting Task Sequencing in Adaptive Intelligent Tutoring Systems. EC-TEL Ruth Janning, Carlotta Schatten, Lars Schmidt-Thieme
2014	—	`conf`	Improved Questionnaire Trees for Active Learning in Recommender Systems. LWA Rasoul Karimi, Alexandros Nanopoulos, Lars Schmidt-Thieme
2014	J	`jnl`	Invariant time-series factorization. Data Min. Knowl. Discov. Josif Grabocka, Lars Schmidt-Thieme
2014	A*	`conf`	Learning time-series shapelets. KDD Josif Grabocka, Nicolas Schilling, Martin Wistuba, Lars Schmidt-Thieme
2014	Misc	`conf`	Local Feature Extractors Accelerating HNNP for Phoneme Recognition. KI Ruth Janning, Carlotta Schatten, Lars Schmidt-Thieme
2014	B	`conf`	Matrix Factorization Feasibility for Sequencing and Adaptive Support in Intelligent Tutoring Systems. EDM Carlotta Schatten, Ruth Janning, Manolis Mavrikis, Lars Schmidt-Thieme
2014	B	`conf`	Minimal Invasive Integration of Learning Analytics Services in Intelligent Tutoring Systems. ICALT Carlotta Schatten, Martin Wistuba, Lars Schmidt-Thieme, Sergio Gutiérrez Santos
2014	—	`conf`	Multimodal Affect Recognition for Adaptive Intelligent Tutoring Systems. EDM (Workshops) Ruth Janning, Carlotta Schatten, Lars Schmidt-Thieme
2014	A	`conf`	Optimizing Multi-Relational Factorization Models for Multiple Target Relations. CIKM Lucas Rêgo Drumond, Ernesto Diaz-Aviles, Lars Schmidt-Thieme, Wolfgang Nejdl
2014	—	`conf`	Realistic optimal policies for energy-efficient train driving. ITSC Josif Grabocka, Alexandros Dalkalitsis, Athanasios Lois, Evangelos Katsaros, Lars Schmidt-Thieme
2014	—	`conf`	Supervised Nonlinear Factorizations Excel In Semi-supervised Regression. PAKDD (1) Josif Grabocka, Erind Bedalli, Lars Schmidt-Thieme
2014	—	`conf`	Vygotsky Based Sequencing Without Domain Information: A Matrix Factorization Approach. CSEDU (Selected Papers) Carlotta Schatten, Ruth Janning, Lars Schmidt-Thieme
2013	—	`ch.`	An Evaluation Measure for Learning from Imbalanced Data Based on Asymmetric Beta Distribution. Classification and Data Mining Nguyen Thai-Nghe, Zeno Gantner, Lars Schmidt-Thieme
2013	—	`conf`	Analysing the Potential Impact of Labeling Disagreements for Engineering Sensor Data. LWA André Busche, Ruth Janning, Lars Schmidt-Thieme
2013	—	`conf`	Event Prediction in Pharyngeal High-Resolution Manometry. ECDA Nicolas Schilling, André Busche, Simone Miller, Michael Jungheim, Martin Ptok, Lars Schmidt-Thieme
2013	B	`conf`	Factorized Decision Trees for Active Learning in Recommender Systems. ICTAI Rasoul Karimi, Martin Wistuba, Alexandros Nanopoulos, Lars Schmidt-Thieme
2013	B	`conf`	HNNP - A Hybrid Neural Network Plait for Improving Image Classification with Additional Side Information. ICTAI Ruth Janning, Carlotta Schatten, Lars Schmidt-Thieme
2013	—	`conf`	Hough Transform and Kirchhoff Migration for Supervised GPR Data Analysis. ECDA André Busche, Daniel Seyfried, Lars Schmidt-Thieme
2013	J	`jnl`	Invariant Factorization Of Time-Series. CoRR Josif Grabocka, Lars Schmidt-Thieme
2013	Misc	`conf`	Move Prediction in Go - Modelling Feature Interactions Using Latent Factors. KI Martin Wistuba, Lars Schmidt-Thieme
2013	—	`conf`	P2P RVM for Distributed Classification. ECDA Muhammad Umer Khan, Alexandros Nanopoulos, Lars Schmidt-Thieme
2013	—	`conf`	Supervised Clustering of Social Media Streams. MediaEval Martin Wistuba, Lars Schmidt-Thieme
2013	B	`conf`	Supervised Dimensionality Reduction via Nonlinear Target Estimation. DaWaK Josif Grabocka, Lucas Drumond, Lars Schmidt-Thieme
2013	J	`jnl`	Time-Series Classification Through Histograms of Symbolic Polynomials. CoRR Josif Grabocka, Martin Wistuba, Lars Schmidt-Thieme
2013	—	`conf`	Towards Optimal Active Learning for Matrix Factorization in Recommender Systems. LWA Rasoul Karimi, Christoph Freudenthaler, Alexandros Nanopoulos, Lars Schmidt-Thieme
2013	—	`conf`	Towards real-time collaborative filtering for big fast data. WWW (Companion Volume) Ernesto Diaz-Aviles, Wolfgang Nejdl, Lucas Drumond, Lars Schmidt-Thieme
2012	—	`conf`	A Unifying Framework for GPR Image Reconstruction. GfKl André Busche, Ruth Janning, Tomás Horváth, Lars Schmidt-Thieme
2012	J	`jnl`	BPR: Bayesian Personalized Ranking from Implicit Feedback CoRR Steffen Rendle, Christoph Freudenthaler, Zeno Gantner, Lars Schmidt-Thieme
2012	—	`ed.`	Challenges at the Interface of Data Analysis, Computer Science, and Optimization - Proceedings of the 34th Annual Conference of the Gesellschaft für Klassifikation e. V., Karlsruhe, July 21 - 23, 2010 GfKl Wolfgang Gaul, Andreas Geyer-Schulz, Lars Schmidt-Thieme, Jonas Kunze
2012	A*	`conf`	Classification of Sparse Time Series via Supervised Matrix Factorization. AAAI Josif Grabocka, Alexandros Nanopoulos, Lars Schmidt-Thieme
2012	—	`conf`	Efficient Classification of Long Time-Series. ICT Innovations Josif Grabocka, Erind Bedalli, Lars Schmidt-Thieme
2012	A	`conf`	Exploiting the characteristics of matrix factorization for active learning in recommender systems. RecSys Rasoul Karimi, Christoph Freudenthaler, Alexandros Nanopoulos, Lars Schmidt-Thieme
2012	—	`conf`	Factorization techniques for student performance classification and ranking. UMAP Workshops Lucas Drumond, Nguyen Thai-Nghe, Tomás Horváth, Lars Schmidt-Thieme
2012	J	`jnl`	GRAMOFON: General model-selection framework based on networks. Neurocomputing Krisztián Búza, Alexandros Nanopoulos, Tomás Horváth, Lars Schmidt-Thieme
2012	—	`conf`	GamRec: A Clustering Method Using Geometrical Background Knowledge for GPR Data Preprocessing. AIAI (1) Ruth Janning, Tomás Horváth, André Busche, Lars Schmidt-Thieme
2012	—	`conf`	Invariant Time-Series Classification. ECML/PKDD (2) Josif Grabocka, Alexandros Nanopoulos, Lars Schmidt-Thieme
2012	A	`conf`	Multi-relational matrix factorization using bayesian personalized ranking for social network data. WSDM Artus Krohn-Grimberghe, Lucas Drumond, Christoph Freudenthaler, Lars Schmidt-Thieme
2012	—	`conf`	Multinomial SVM Item Recommender for Repeat-Buying Scenarios. GfKl Christina Lichtenthäler, Lars Schmidt-Thieme
2012	—	`conf`	Personalized Ranking for Non-Uniformly Sampled Items. KDD Cup Zeno Gantner, Lucas Drumond, Christoph Freudenthaler, Lars Schmidt-Thieme
2012	Misc	`conf`	Predicting RDF triples in incomplete knowledge bases with tensor factorization. SAC Lucas Drumond, Steffen Rendle, Lars Schmidt-Thieme
2012	A	`conf`	Real-time top-n recommendation in social streams. RecSys Ernesto Diaz-Aviles, Lucas Drumond, Lars Schmidt-Thieme, Wolfgang Nejdl
2012	—	`book`	Recommender Systems for Social Tagging Systems. Leandro Balby Marinho, Andreas Hotho, Robert Jäschke, Alexandros Nanopoulos, Steffen Rendle, Lars Schmidt-Thieme, Gerd Stumme, Panagiotis Symeonidis
2012	—	`conf`	Using factorization machines for student modeling. UMAP Workshops Nguyen Thai-Nghe, Lucas Drumond, Tomás Horváth, Lars Schmidt-Thieme
2012	A	`conf`	What is happening right now ... that interests me?: online topic discovery and recommendation in twitter. CIKM Ernesto Diaz-Aviles, Lucas Drumond, Zeno Gantner, Lars Schmidt-Thieme, Wolfgang Nejdl
2011	B	`conf`	A new evaluation measure for learning from imbalanced data. IJCNN Nguyen Thai-Nghe, Zeno Gantner, Lars Schmidt-Thieme
2011	B	`conf`	Active Learning for Technology Enhanced Learning. EC-TEL Artus Krohn-Grimberghe, André Busche, Alexandros Nanopoulos, Lars Schmidt-Thieme
2011	—	`conf`	Active Learning for Technology Enhanced Learning. LWA Artus Krohn-Grimberghe, André Busche, Alexandros Nanopoulos, Lars Schmidt-Thieme
2011	C	`conf`	Active learning for aspect model in recommender systems. CIDM Rasoul Karimi, Christoph Freudenthaler, Alexandros Nanopoulos, Lars Schmidt-Thieme
2011	B	`conf`	Factorization Models for Forecasting Student Performance. EDM Nguyen Thai-Nghe, Tomás Horváth, Lars Schmidt-Thieme
2011	—	`conf`	Fast Classification of Electrocardiograph Signals via Instance Selection. HISB Krisztián Búza, Alexandros Nanopoulos, Lars Schmidt-Thieme, Júlia Koller
2011	A*	`conf`	Fast context-aware recommendations with factorization machines. SIGIR Steffen Rendle, Zeno Gantner, Christoph Freudenthaler, Lars Schmidt-Thieme
2011	—	`conf`	Fusion of Similarity Measures for Time Series Classification. HAIS (2) Krisztián Búza, Alexandros Nanopoulos, Lars Schmidt-Thieme
2011	—	`conf`	INSIGHT: Efficient and Effective Instance Selection for Time-Series Classification. PAKDD (2) Krisztián Búza, Alexandros Nanopoulos, Lars Schmidt-Thieme
2011	C	`conf`	IQ estimation for accurate time-series classification. CIDM Krisztián Búza, Alexandros Nanopoulos, Lars Schmidt-Thieme
2011	—	`conf`	Keyword-Based TV Program Recommendation. ITWP@IJCAI Christian Wartena, Wout Slakhorst, Martin Wibbels, Zeno Gantner, Christoph Freudenthaler, Chris Newell, Lars Schmidt-Thieme
2011	—	`conf`	Matrix and Tensor Factorization for Predicting Student Performance. CSEDU (1) Nguyen Thai-Nghe, Lucas Drumond, Tomás Horváth, Alexandros Nanopoulos, Lars Schmidt-Thieme
2011	A	`conf`	MyMediaLite: a free recommender system library. RecSys Zeno Gantner, Steffen Rendle, Christoph Freudenthaler, Lars Schmidt-Thieme
2011	Misc	`conf`	Non-myopic active learning for recommender systems based on Matrix Factorization. IRI Rasoul Karimi, Christoph Freudenthaler, Alexandros Nanopoulos, Lars Schmidt-Thieme
2011	B	`conf`	Personalized Forecasting Student Performance. ICALT Nguyen Thai-Nghe, Tomás Horváth, Lars Schmidt-Thieme
2011	—	`conf`	RFID-Enhanced Museum for Interactive Experience. MM4CH Rasoul Karimi, Alexandros Nanopoulos, Lars Schmidt-Thieme
2011	A	`conf`	Scalable Event-Based Clustering of Social Media Via Record Linkage Techniques. ICWSM Timo Reuter, Philipp Cimiano, Lucas Drumond, Krisztián Búza, Lars Schmidt-Thieme
2011	—	`ch.`	Social Tagging Recommender Systems. Recommender Systems Handbook Leandro Balby Marinho, Alexandros Nanopoulos, Lars Schmidt-Thieme, Robert Jäschke, Andreas Hotho, Gerd Stumme, Panagiotis Symeonidis
2011	B	`conf`	Towards Optimal Active Learning for Matrix Factorization in Recommender Systems. ICTAI Rasoul Karimi, Christoph Freudenthaler, Alexandros Nanopoulos, Lars Schmidt-Thieme
2010	—	`conf`	A Novel Multidimensional Framework for Evaluating Recommender Systems. LWA Artus Krohn-Grimberghe, Alexandros Nanopoulos, Lars Schmidt-Thieme
2010	B	`conf`	Cost-sensitive learning methods for imbalanced data. IJCNN Nguyen Thai-Nghe, Zeno Gantner, Lars Schmidt-Thieme
2010	A*	`conf`	Factorizing personalized Markov chains for next-basket recommendation. WWW Steffen Rendle, Christoph Freudenthaler, Lars Schmidt-Thieme
2010	—	`conf`	Graph-Based Model-Selection Framework for Large Ensembles. HAIS (1) Krisztián Búza, Alexandros Nanopoulos, Lars Schmidt-Thieme
2010	—	`conf`	Individualized Error Estimation for Classification and Regression Models. GfKl Krisztián Búza, Alexandros Nanopoulos, Lars Schmidt-Thieme
2010	C	`conf`	Integrating OLAP and recommender systems: an evaluation perspective. DOLAP Artus Krohn-Grimberghe, Alexandros Nanopoulos, Lars Schmidt-Thieme
2010	A*	`conf`	Learning Attribute-to-Feature Mappings for Cold-Start Recommendations. ICDM Zeno Gantner, Lucas Drumond, Christoph Freudenthaler, Steffen Rendle, Lars Schmidt-Thieme
2010	—	`conf`	Mining Music Playlogs for Next Song Recommendations. LWA André Busche, Artus Krohn-Grimberghe, Lars Schmidt-Thieme
2010	A	`conf`	Pairwise interaction tensor factorization for personalized tag recommendation. WSDM Steffen Rendle, Lars Schmidt-Thieme
2010	—	`conf`	Recommender system for predicting student performance. RecSysTEL@RecSys Nguyen Thai-Nghe, Lucas Drumond, Artus Krohn-Grimberghe, Lars Schmidt-Thieme
2010	—	`conf`	Semi-supervised Tag Recommendation - Using Untagged Resources to Mitigate Cold-Start Problems. PAKDD (1) Christine Preisach, Leandro Balby Marinho, Lars Schmidt-Thieme
2010	—	`conf`	Time-Series Classification Based on Individualised Error Prediction. CSE Krisztián Búza, Alexandros Nanopoulos, Lars Schmidt-Thieme
2010	A	`conf`	Workshop on user-centric evaluation of recommender systems and their interfaces. RecSys Bart P. Knijnenburg, Lars Schmidt-Thieme, Dirk G. F. M. Bollen
2009	—	`conf`	Automatic Content-Based Categorization of Wikipedia Articles. PWNLP@IJCNLP Zeno Gantner, Lars Schmidt-Thieme
2009	A	`conf`	BPR: Bayesian Personalized Ranking from Implicit Feedback. UAI Steffen Rendle, Christoph Freudenthaler, Zeno Gantner, Lars Schmidt-Thieme
2009	—	`conf`	Cross-tagging for personalized open social networking. Hypertext Avare Stewart, Ernesto Diaz-Aviles, Wolfgang Nejdl, Leandro Balby Marinho, Alexandros Nanopoulos, Lars Schmidt-Thieme
2009	—	`conf`	Factor Models for Tag Recommendation in BibSonomy. DC@PKDD/ECML Steffen Rendle, Lars Schmidt-Thieme
2009	C	`conf`	Improving Academic Performance Prediction by Dealing with Class Imbalance. ISDA Nguyen Thai-Nghe, André Busche, Lars Schmidt-Thieme
2009	A*	`conf`	Learning optimal ranking with tensor factorization for tag recommendation. KDD Steffen Rendle, Leandro Balby Marinho, Alexandros Nanopoulos, Lars Schmidt-Thieme
2009	B	`conf`	Learning to Extract Relations for Relational Classification. PAKDD Steffen Rendle, Christine Preisach, Lars Schmidt-Thieme
2009	—	`conf`	Optimal Ranking for Video Recommendation. UCMedia Zeno Gantner, Christoph Freudenthaler, Steffen Rendle, Lars Schmidt-Thieme
2009	A	`ed.`	Proceedings of the 2009 ACM Conference on Recommender Systems, RecSys 2009, New York, NY, USA, October 23-25, 2009 RecSys Lawrence D. Bergman, Alexander Tuzhilin, Robin D. Burke, Alexander Felfernig, Lars Schmidt-Thieme
2009	—	`conf`	Relational Classification for Personalized Tag Recommendation. DC@PKDD/ECML Leandro Balby Marinho, Christine Preisach, Lars Schmidt-Thieme
2009	A	`conf`	Swarming to rank for information retrieval. GECCO Ernesto Diaz-Aviles, Wolfgang Nejdl, Lars Schmidt-Thieme
2008	A*	`conf`	Active Learning of Equivalence Relations by Minimizing the Expected Loss Using Constraint Inference. ICDM Steffen Rendle, Lars Schmidt-Thieme
2008	—	`ed.`	Data Analysis, Machine Learning and Applications - Proceedings of the 31st Annual Conference of the Gesellschaft für Klassifikation e.V., Albert-Ludwigs-Universität Freiburg, March 7-9, 2007 GfKl Christine Preisach, Hans Burkhardt, Lars Schmidt-Thieme, Reinhold Decker
2008	J	`jnl`	Emergence of Spontaneous Order Through Neighborhood Formation in Peer-to-Peer Recommender Systems CoRR Ernesto Diaz-Aviles, Lars Schmidt-Thieme, Cai-Nicolas Ziegler
2008	J	`jnl`	Ensembles of relational classifiers. Knowl. Inf. Syst. Christine Preisach, Lars Schmidt-Thieme
2008	Misc	`conf`	Folksonomy-Based Collabulary Learning. ISWC Leandro Balby Marinho, Krisztián Búza, Lars Schmidt-Thieme
2008	—	`conf`	Motif-Based Classification of Time Series with Bayesian Networks and SVMs. GfKl Krisztián Búza, Lars Schmidt-Thieme
2008	A	`conf`	Online-updating regularized kernel matrix factorization models for large-scale recommender systems. RecSys Steffen Rendle, Lars Schmidt-Thieme
2008	B	`conf`	Scaling Record Linkage to Non-uniform Distributed Class Sizes. PAKDD Steffen Rendle, Lars Schmidt-Thieme
2008	J	`jnl`	Tag recommendations in social bookmarking systems. AI Commun. Robert Jäschke, Leandro Balby Marinho, Andreas Hotho, Lars Schmidt-Thieme, Gerd Stumme
2008	Misc	`conf`	Tag-aware recommender systems by fusion of collaborative filtering algorithms. SAC Karen H. L. Tso-Sutter, Leandro Balby Marinho, Lars Schmidt-Thieme
2007	—	`conf`	Collaborative Tag Recommendations. GfKl Leandro Balby Marinho, Lars Schmidt-Thieme
2007	C	`conf`	Combining multi-distributed mixture models and bayesian networks for semi-supervised learning. ICMLA Manuel Stritt, Lars Schmidt-Thieme, Gerhard Poeppel
2007	—	`conf`	Comparison of Recommender System Algorithms Focusing on the New-item and User-bias Problem. GfKl Stefan Hauger, Karen H. L. Tso, Lars Schmidt-Thieme
2007	J	`jnl`	Guest Editors' Introduction: Recommender Systems. IEEE Intell. Syst. Alexander Felfernig, Gerhard Friedrich, Lars Schmidt-Thieme
2007	—	`conf`	Information Integration of Partially Labeled Data. GfKl Steffen Rendle, Lars Schmidt-Thieme
2007	J	`jnl`	Supporting collaborative hierarchical classification: Bookmarks as an example. Comput. Networks Dominik Benz, Karen H. L. Tso, Lars Schmidt-Thieme
2007	—	`conf`	Tag Recommendations in Folksonomies. LWA Robert Jäschke, Leandro Balby Marinho, Andreas Hotho, Lars Schmidt-Thieme, Gerd Stumme
2007	—	`conf`	Tag Recommendations in Folksonomies. PKDD Robert Jäschke, Leandro Balby Marinho, Andreas Hotho, Lars Schmidt-Thieme, Gerd Stumme
2006	J	`jnl`	A Bottom-up approach to Grid-Computing at a University: the Black-Forest-Grid Initiative. Prax. Inf.verarb. Kommun. Rolf Backofen, Hans-Gunther Borrmann, Werner Deck, Andreas Dedner, Luc De Raedt, Klaus Desch, Markus Diesmann, Martin Geier, Andreas Greiner, Wolfgang R. Hess, Josef Honerkamp, Stefan Jankowski, Ingo Krossing, Andreas W. Liehr, Andreas Karwath, Robert Klöfkorn, Raphaël Pesché, Tobias C. Potjans, Michael C. Röttger, Lars Schmidt-Thieme, Gerhard Schneider, Björn Voß, Bernd Wiebelt, Peter Wienemann, Volker-Henning Winterer
2006	—	`conf`	Attribute Aware Anonymous Recommender Systems. GfKl Manuel Stritt, Karen H. L. Tso, Lars Schmidt-Thieme
2006	—	`ch.`	Empirical Analysis of Attribute-Aware Recommendation Algorithms with Variable Synthetic Data. Data Science and Classification Karen H. L. Tso, Lars Schmidt-Thieme
2006	J	`jnl`	Empirical Analysis of Attribute-Aware Recommender System Algorithms Using Synthetic Data. J. Comput. Karen H. L. Tso, Lars Schmidt-Thieme
2006	B	`conf`	Evaluation of Attribute-Aware Recommender System Algorithms on Data with Varying Characteristics. PAKDD Karen H. L. Tso, Lars Schmidt-Thieme
2006	B	`conf`	Ideas and Improvements for Semantic Wikis. ESWC Jochen Fischer, Zeno Gantner, Steffen Rendle, Manuel Stritt, Lars Schmidt-Thieme
2006	A*	`conf`	Object Identification with Constraints. ICDM Steffen Rendle, Lars Schmidt-Thieme
2006	A*	`conf`	Relational Ensemble Classification. ICDM Christine Preisach, Lars Schmidt-Thieme
2005	—	`conf`	Attribute-aware Collaborative Filtering. GfKl Karen H. L. Tso, Lars Schmidt-Thieme
2005	B	`conf`	Collaborative and Usage-Driven Evolution of Personal Ontologies. ESWC Peter Haase, Andreas Hotho, Lars Schmidt-Thieme, York Sure
2005	—	`conf`	Collaborative and Usage-driven Evolution of Personal Ontologies. LWA Peter Haase, Andreas Hotho, Lars Schmidt-Thieme, York Sure
2005	A*	`conf`	Compound Classification Models for Recommender Systems. ICDM Lars Schmidt-Thieme
2005	—	`book`	Data Analysis and Decision Support Daniel Baier, Reinhold Decker, Lars Schmidt-Thieme
2005	—	`conf`	Fachinformationssystem Informatik (FIS-I) und Semantische Technologien für Informationsportale (SemIPort). GI Jahrestagung (2) Peter Fankhauser, Norbert Fuhr, Jens Hartmann, Anthony Jameson, Claus-Peter Klas, Stefan Klink, Agnes Koschmider, Sascha Kriewel, Patrick Lehti, Peter Luksch, Ernst W. Mayr, Andreas Oberweis, Paul Ortyl, Stefan Pfingstl, Patrick Reuther, Ute Rusnak, Guido Sautter, Klemens Böhm, André Schaefer, Lars Schmidt-Thieme, Eric Schwarzkopf, Nenad Stojanovic, Rudi Studer, Roland Vollmar, Bernd Walter, Alexander Weber
2005	—	`conf`	Ontology-Based Query Refinement for Semantic Portals. From Integrated Publication and Information Systems to Virtual Information and Knowledge Environments Jens Hartmann, Nenad Stojanovic, Rudi Studer, Lars Schmidt-Thieme
2005	—	`ch.`	Performance Drivers for Depth-First Frequent Pattern Mining. Data Analysis and Decision Support Lars Schmidt-Thieme, Martin Schader
2005	—	`conf`	The Relation of Closed Itemset Mining, Complete Pruning Strategies and Item Ordering in Apriori-Based FIM Algorithms. PKDD Ferenc Bodon, Lars Schmidt-Thieme
2004	—	`conf`	Algorithmic Features of Eclat. FIMI Lars Schmidt-Thieme
2004	—	`conf`	Reservation Price Estimation by Adaptive Conjoint Analysis. GfKl Christoph Breidert, Michael Hahsler, Lars Schmidt-Thieme
2004	A	`conf`	Taxonomy-driven computation of product recommendations. CIKM Cai-Nicolas Ziegler, Georg Lausen, Lars Schmidt-Thieme
2003	—	`—`	Assoziationsregel-Algorithmen für Daten mit komplexer Struktur: mit Anwendungen im Web Mining. Lars Schmidt-Thieme
2003	—	`book`	Java - eine Einführung (4. Aufl.). Martin Schader, Lars Schmidt-Thieme
2001	A*	`conf`	Mining Generalized Association Rules for Sequential and Path Data. ICDM Wolfgang Gaul, Lars Schmidt-Thieme