Alexander J. Smola

324 papers A* 77A 39B 7C 2Journal 111Unranked 86

Year	Rank	Type	Title / Venue / Authors
2024	J	`jnl`	Improving Semantic Segmentation via Efficient Self-Training. IEEE Trans. Pattern Anal. Mach. Intell. Yi Zhu, Zhongyue Zhang, Chongruo Wu, Zhi Zhang, Tong He, Hang Zhang, R. Manmatha, Mu Li, Alexander J. Smola
2023	J	`jnl`	Flexible Model Aggregation for Quantile Regression. J. Mach. Learn. Res. Rasool Fakoor, Taesup Kim, Jonas Mueller, Alexander J. Smola, Ryan J. Tibshirani
2023	A*	`conf`	Prompt Pre-Training with Twenty-Thousand Classes for Open-Vocabulary Visual Recognition. NeurIPS Shuhuai Ren, Aston Zhang, Yi Zhu, Shuai Zhang, Shuai Zheng, Mu Li, Alexander J. Smola, Xu Sun
2022	A*	`conf`	Adaptive Interest for Emphatic Reinforcement Learning. NeurIPS Martin Klissarov, Rasool Fakoor, Jonas W. Mueller, Kavosh Asadi, Taesup Kim, Alexander J. Smola
2022	A*	`conf`	BLISS: A Billion scale Index using Iterative Re-partitioning. KDD Gaurav Gupta, Tharun Medini, Anshumali Shrivastava, Alexander J. Smola
2022	J	`jnl`	Data drift correction via time-varying importance weight estimator. CoRR Rasool Fakoor, Jonas Mueller, Zachary C. Lipton, Pratik Chaudhari, Alexander J. Smola
2022	A*	`conf`	Faster Deep Reinforcement Learning with Slower Online Network. NeurIPS Kavosh Asadi, Rasool Fakoor, Omer Gottesman, Taesup Kim, Michael L. Littman, Alexander J. Smola
2022	A*	`conf`	Graph Reordering for Cache-Efficient Near Neighbor Search. NeurIPS Benjamin Coleman, Santiago Segarra, Alexander J. Smola, Anshumali Shrivastava
2022	J	`jnl`	GraphHINGE: Learning Interaction Models of Structured Neighborhood on Heterogeneous Information Network. ACM Trans. Inf. Syst. Jiarui Jin, Kounianhua Du, Weinan Zhang, Jiarui Qin, Yuchen Fang, Yong Yu, Zheng Zhang, Alexander J. Smola
2022	A*	`conf`	Multimodal AutoML for Image, Text and Tabular Data. KDD Nick Erickson, Xingjian Shi, James Sharpnack, Alexander J. Smola
2022	—	`conf`	ResNeSt: Split-Attention Networks. CVPR Workshops Hang Zhang, Chongruo Wu, Zhongyue Zhang, Yi Zhu, Haibin Lin, Zhi Zhang, Yue Sun, Tong He, Jonas Mueller, R. Manmatha, Mu Li, Alexander J. Smola
2021	—	`conf`	Benchmarking Multimodal AutoML for Tabular Data with Text Fields. NeurIPS Datasets and Benchmarks Xingjian Shi, Jonas Mueller, Nick Erickson, Mu Li, Alexander J. Smola
2021	J	`jnl`	Benchmarking Multimodal AutoML for Tabular Data with Text Fields. CoRR Xingjian Shi, Jonas Mueller, Nick Erickson, Mu Li, Alexander J. Smola
2021	A*	`conf`	Continuous Doubly Constrained Batch Reinforcement Learning. NeurIPS Rasool Fakoor, Jonas Mueller, Kavosh Asadi, Pratik Chaudhari, Alexander J. Smola
2021	J	`jnl`	Continuous Doubly Constrained Batch Reinforcement Learning. CoRR Rasool Fakoor, Jonas Mueller, Pratik Chaudhari, Alexander J. Smola
2021	A*	`conf`	Deep Explicit Duration Switching Models for Time Series. NeurIPS Abdul Fatir Ansari, Konstantinos Benidis, Richard Kurle, Ali Caner Türkmen, Harold Soh, Alexander J. Smola, Bernie Wang, Tim Januschowski
2021	J	`jnl`	Deep Explicit Duration Switching Models for Time Series. CoRR Abdul Fatir Ansari, Konstantinos Benidis, Richard Kurle, Ali Caner Türkmen, Harold Soh, Alexander J. Smola, Yuyang Wang, Tim Januschowski
2021	J	`jnl`	Deep Q-Network with Proximal Iteration. CoRR Kavosh Asadi, Rasool Fakoor, Omer Gottesman, Michael L. Littman, Alexander J. Smola
2021	J	`jnl`	Deep Quantile Aggregation. CoRR Taesup Kim, Rasool Fakoor, Jonas Mueller, Alexander J. Smola, Ryan J. Tibshirani
2021	J	`jnl`	Dive into Deep Learning. CoRR Aston Zhang, Zachary C. Lipton, Mu Li, Alexander J. Smola
2021	J	`jnl`	IRLI: Iterative Re-partitioning for Learning to Index. CoRR Gaurav Gupta, Tharun Medini, Anshumali Shrivastava, Alexander J. Smola
2021	A*	`conf`	Mixture Proportion Estimation and PU Learning: A Modern Approach. NeurIPS Saurabh Garg, Yifan Wu, Alexander J. Smola, Sivaraman Balakrishnan, Zachary C. Lipton
2021	A*	`conf`	Symbolic Music Generation with Transformer-GANs. AAAI Aashiq Muhamed, Liang Li, Xingjian Shi, Suri Yaddanapudi, Wayne Chi, Dylan Jackson, Rahul Suresh, Zachary C. Lipton, Alexander J. Smola
2020	A*	`conf`	An Efficient Neighborhood-based Interaction Model for Recommendation on Heterogeneous Graph. KDD Jiarui Jin, Jiarui Qin, Yuchen Fang, Kounianhua Du, Weinan Zhang, Yong Yu, Zheng Zhang, Alexander J. Smola
2020	J	`jnl`	An Efficient Neighborhood-based Interaction Model for Recommendation on Heterogeneous Graph. CoRR Jiarui Jin, Jiarui Qin, Yuchen Fang, Kounianhua Du, Weinan Zhang, Yong Yu, Zheng Zhang, Alexander J. Smola
2020	J	`jnl`	AutoGluon-Tabular: Robust and Accurate AutoML for Structured Data. CoRR Nick Erickson, Jonas Mueller, Alexander Shirkov, Hang Zhang, Pedro Larroy, Mu Li, Alexander J. Smola
2020	J	`jnl`	Bloom Origami Assays: Practical Group Testing. CoRR Louis Abraham, Gary Bécigneul, Benjamin Coleman, Bernhard Schölkopf, Anshumali Shrivastava, Alexander J. Smola
2020	J	`jnl`	DDPG++: Striving for Simplicity in Continuous-control Off-Policy Reinforcement Learning. CoRR Rasool Fakoor, Pratik Chaudhari, Alexander J. Smola
2020	A*	`conf`	Fast, Accurate, and Simple Models for Tabular Data via Augmented Distillation. NeurIPS Rasool Fakoor, Jonas Mueller, Nick Erickson, Pratik Chaudhari, Alexander J. Smola
2020	J	`jnl`	Fast, Accurate, and Simple Models for Tabular Data via Augmented Distillation. CoRR Rasool Fakoor, Jonas Mueller, Nick Erickson, Pratik Chaudhari, Alexander J. Smola
2020	A*	`conf`	Faster, Simpler, More Accurate: Practical Automated Machine Learning with Tabular, Text, and Image Data. KDD Jonas Mueller, Xingjian Shi, Alexander J. Smola
2020	J	`jnl`	Improving Semantic Segmentation via Self-Training. CoRR Yi Zhu, Zhongyue Zhang, Chongruo Wu, Zhi Zhang, Tong He, Hang Zhang, R. Manmatha, Mu Li, Alexander J. Smola
2020	J	`jnl`	Learning Interaction Models of Structured Neighborhood on Heterogeneous Information Network. CoRR Jiarui Jin, Kounianhua Du, Weinan Zhang, Jiarui Qin, Yuchen Fang, Yong Yu, Zheng Zhang, Alexander J. Smola
2020	A*	`conf`	Meta-Q-Learning. ICLR Rasool Fakoor, Pratik Chaudhari, Stefano Soatto, Alexander J. Smola
2020	J	`jnl`	ResNeSt: Split-Attention Networks. CoRR Hang Zhang, Chongruo Wu, Zhongyue Zhang, Yi Zhu, Zhi Zhang, Haibin Lin, Yue Sun, Tong He, Jonas Mueller, R. Manmatha, Mu Li, Alexander J. Smola
2020	J	`jnl`	TraDE: Transformers for Density Estimation. CoRR Rasool Fakoor, Pratik Chaudhari, Jonas Mueller, Alexander J. Smola
2020	J	`jnl`	Transformer on a Diet. CoRR Chenguang Wang, Zihao Ye, Aston Zhang, Zheng Zhang, Alexander J. Smola
2019	J	`jnl`	Deep Graph Library: Towards Efficient and Scalable Deep Learning on Graphs. CoRR Minjie Wang, Lingfan Yu, Da Zheng, Quan Gan, Yu Gai, Zihao Ye, Mufei Li, Jinjing Zhou, Qi Huang, Chao Ma, Ziyue Huang, Qipeng Guo, Hao Zhang, Haibin Lin, Junbo Zhao, Jinyang Li, Alexander J. Smola, Zheng Zhang
2019	—	`conf`	Dive into Deep Learning for Natural Language Processing. EMNLP/IJCNLP (2) Haibin Lin, Xingjian Shi, Leonard Lausen, Aston Zhang, He He, Sheng Zha, Alexander J. Smola
2019	A	`conf`	Efficient Multitask Feature and Relationship Learning. UAI Han Zhao, Otilia Stretcu, Alexander J. Smola, Geoffrey J. Gordon
2019	—	`conf`	FastPoint: Scalable Deep Point Processes. ECML/PKDD (2) Ali Caner Türkmen, Yuyang Wang, Alexander J. Smola
2019	J	`jnl`	Language Models with Transformers. CoRR Chenguang Wang, Mu Li, Alexander J. Smola
2019	J	`jnl`	Meta-Q-Learning. CoRR Rasool Fakoor, Pratik Chaudhari, Stefano Soatto, Alexander J. Smola
2019	A	`conf`	P3O: Policy-on Policy-off Policy Optimization. UAI Rasool Fakoor, Pratik Chaudhari, Alexander J. Smola
2019	J	`jnl`	P3O: Policy-on Policy-off Policy Optimization. CoRR Rasool Fakoor, Pratik Chaudhari, Alexander J. Smola
2018	A	`conf`	A Generic Approach for Escaping Saddle points. AISTATS Sashank J. Reddi, Manzil Zaheer, Suvrit Sra, Barnabás Póczos, Francis R. Bach, Ruslan Salakhutdinov, Alexander J. Smola
2018	A*	`conf`	Compressed Video Action Recognition. CVPR Chao-Yuan Wu, Manzil Zaheer, Hexiang Hu, R. Manmatha, Alexander J. Smola, Philipp Krähenbühl
2018	A*	`conf`	Detecting and Correcting for Label Shift with Black Box Predictors. ICML Zachary C. Lipton, Yu-Xiang Wang, Alexander J. Smola
2018	J	`jnl`	Detecting and Correcting for Label Shift with Black Box Predictors. CoRR Zachary C. Lipton, Yu-Xiang Wang, Alexander J. Smola
2018	A*	`conf`	Learning Steady-States of Iterative Algorithms over Graphs. ICML Hanjun Dai, Zornitsa Kozareva, Bo Dai, Alexander J. Smola, Le Song
2018	A*	`conf`	Variational Reasoning for Question Answering With Knowledge Graph. AAAI Yuyu Zhang, Hanjun Dai, Zornitsa Kozareva, Alexander J. Smola, Le Song
2017	J	`jnl`	A Generic Approach for Escaping Saddle points. CoRR Sashank J. Reddi, Manzil Zaheer, Suvrit Sra, Barnabás Póczos, Francis R. Bach, Ruslan Salakhutdinov, Alexander J. Smola
2017	A	`conf`	Attributing Hacks. AISTATS Ziqi Liu, Alexander J. Smola, Kyle Soska, Yu-Xiang Wang, Qinghua Zheng
2017	A*	`conf`	Canopy Fast Sampling with Cover Trees. ICML Manzil Zaheer, Satwik Kottur, Amr Ahmed, José M. F. Moura, Alexander J. Smola
2017	J	`jnl`	Compressed Video Action Recognition. CoRR Chao-Yuan Wu, Manzil Zaheer, Hexiang Hu, R. Manmatha, Alexander J. Smola, Philipp Krähenbühl
2017	—	`conf`	Data Driven Resource Allocation for Distributed Learning. AAAI Workshops Travis Dick, Mu Li, Venkata Krishna Pillutla, Colin White, Maria-Florina Balcan, Alexander J. Smola
2017	A	`conf`	Data Driven Resource Allocation for Distributed Learning. AISTATS Travis Dick, Mu Li, Venkata Krishna Pillutla, Colin White, Nina Balcan, Alexander J. Smola
2017	—	`conf`	Deep Sets. NIPS Manzil Zaheer, Satwik Kottur, Siamak Ravanbakhsh, Barnabás Póczos, Ruslan Salakhutdinov, Alexander J. Smola
2017	J	`jnl`	Deep Sets. CoRR Manzil Zaheer, Satwik Kottur, Siamak Ravanbakhsh, Barnabás Póczos, Ruslan Salakhutdinov, Alexander J. Smola
2017	J	`jnl`	Efficient Multi-task Feature and Relationship Learning. CoRR Han Zhao, Otilia Stretcu, Renato Negrinho, Alexander J. Smola, Geoffrey J. Gordon
2017	J	`jnl`	F2F: A Library For Fast Kernel Expansions. CoRR Joachim de Curtò, Irene Zarza, Feng Yang, Alexander J. Smola, Luc Van Gool
2017	—	`conf`	Generative Models and Model Criticism via Optimized Maximum Mean Discrepancy. ICLR (Poster) Danica J. Sutherland, Hsiao-Yu Tung, Heiko Strathmann, Soumyajit De, Aaditya Ramdas, Alexander J. Smola, Arthur Gretton
2017	J	`jnl`	Go for a Walk and Arrive at the Answer: Reasoning Over Paths in Knowledge Bases using Reinforcement Learning. CoRR Rajarshi Das, Shehzaad Dhuliawala, Manzil Zaheer, Luke Vilnis, Ishan Durugkar, Akshay Krishnamurthy, Alexander J. Smola, Andrew McCallum
2017	J	`jnl`	HashBox: Hash Hierarchical Segmentation exploiting Bounding Box Object Detection. CoRR Joachim de Curtò, Irene Zarza, Alexander J. Smola, Luc Van Gool
2017	—	`conf`	Joint Training of Ratings and Reviews with Recurrent Recommender Networks. ICLR (Workshop) Chao-Yuan Wu, Amr Ahmed, Alex Beutel, Alexander J. Smola
2017	A*	`conf`	Latent LSTM Allocation: Joint Clustering and Non-Linear Dynamic Modeling of Sequence Data. ICML Manzil Zaheer, Amr Ahmed, Alexander J. Smola
2017	—	`conf`	Neural Machine Translation with Recurrent Attention Modeling. EACL (2) Zichao Yang, Zhiting Hu, Yuntian Deng, Chris Dyer, Alexander J. Smola
2017	A	`conf`	Neural Survival Recommender. WSDM How Jing, Alexander J. Smola
2017	A	`conf`	Recurrent Recommender Networks. WSDM Chao-Yuan Wu, Amr Ahmed, Alex Beutel, Alexander J. Smola, How Jing
2017	A*	`conf`	Sampling Matters in Deep Embedding Learning. ICCV R. Manmatha, Chao-Yuan Wu, Alexander J. Smola, Philipp Krähenbühl
2017	J	`jnl`	Sampling Matters in Deep Embedding Learning. CoRR Chao-Yuan Wu, R. Manmatha, Alexander J. Smola, Philipp Krähenbühl
2017	J	`jnl`	Spectral Methods for Nonparametric Models. CoRR Hsiao-Yu Fish Tung, Chao-Yuan Wu, Manzil Zaheer, Alexander J. Smola
2017	J	`jnl`	State Space LSTM Models with Particle MCMC Inference. CoRR Xun Zheng, Manzil Zaheer, Amr Ahmed, Yuan Wang, Eric P. Xing, Alexander J. Smola
2017	J	`jnl`	Variational Reasoning for Question Answering with Knowledge Graph. CoRR Yuyu Zhang, Hanjun Dai, Zornitsa Kozareva, Alexander J. Smola, Le Song
2016	J	`jnl`	AIDE: Fast and Communication Efficient Distributed Optimization. CoRR Sashank J. Reddi, Jakub Konecný, Peter Richtárik, Barnabás Póczos, Alexander J. Smola
2016	A	`conf`	AdaDelay: Delay Adaptive Distributed Stochastic Optimization. AISTATS Suvrit Sra, Adams Wei Yu, Mu Li, Alexander J. Smola
2016	J	`jnl`	Attributing Hacks. CoRR Ziqi Liu, Alexander J. Smola, Kyle Soska, Yu-Xiang Wang, Qinghua Zheng
2016	A	`conf`	DiFacto: Distributed Factorization Machines. WSDM Mu Li, Ziqi Liu, Alexander J. Smola, Yu-Xiang Wang
2016	—	`conf`	Explaining Reviews and Ratings with PACO: Poisson Additive Co-Clustering. WWW (Companion Volume) Chao-Yuan Wu, Alex Beutel, Amr Ahmed, Alexander J. Smola
2016	A	`conf`	Exponential Stochastic Cellular Automata for Massively Parallel Inference. AISTATS Manzil Zaheer, Michael L. Wick, Jean-Baptiste Tristan, Alexander J. Smola, Guy L. Steele Jr.
2016	J	`jnl`	Fast Incremental Method for Nonconvex Optimization. CoRR Sashank J. Reddi, Suvrit Sra, Barnabás Póczos, Alexander J. Smola
2016	J	`jnl`	Fast Stochastic Methods for Nonsmooth Nonconvex Optimization. CoRR Sashank J. Reddi, Suvrit Sra, Barnabás Póczos, Alexander J. Smola
2016	—	`conf`	Fast incremental method for smooth nonconvex optimization. CDC Sashank J. Reddi, Suvrit Sra, Barnabás Póczos, Alexander J. Smola
2016	J	`jnl`	Gaussian Processes for Independence Tests with Non-iid Data in Causal Inference. ACM Trans. Intell. Syst. Technol. Seth R. Flaxman, Daniel B. Neill, Alexander J. Smola
2016	J	`jnl`	Generative Models and Model Criticism via Optimized Maximum Mean Discrepancy. CoRR Danica J. Sutherland, Hsiao-Yu Fish Tung, Heiko Strathmann, Soumyajit De, Aaditya Ramdas, Alexander J. Smola, Arthur Gretton
2016	—	`conf`	Hierarchical Attention Networks for Document Classification. HLT-NAACL Zichao Yang, Diyi Yang, Chris Dyer, Xiaodong He, Alexander J. Smola, Eduard H. Hovy
2016	J	`jnl`	Neural Machine Translation with Recurrent Attention Modeling. CoRR Zichao Yang, Zhiting Hu, Yuntian Deng, Chris Dyer, Alexander J. Smola
2016	A*	`ed.`	Proceedings of the 22nd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, San Francisco, CA, USA, August 13-17, 2016 KDD Balaji Krishnapuram, Mohak Shah, Alexander J. Smola, Charu C. Aggarwal, Dou Shen, Rajeev Rastogi
2016	—	`conf`	Proximal Stochastic Methods for Nonsmooth Nonconvex Finite-Sum Optimization. NIPS Sashank J. Reddi, Suvrit Sra, Barnabás Póczos, Alexander J. Smola
2016	A*	`conf`	Stacked Attention Networks for Image Question Answering. CVPR Zichao Yang, Xiaodong He, Jianfeng Gao, Li Deng, Alexander J. Smola
2016	J	`jnl`	Stochastic Frank-Wolfe Methods for Nonconvex Optimization. CoRR Sashank J. Reddi, Suvrit Sra, Barnabás Póczos, Alexander J. Smola
2016	—	`conf`	Stochastic Frank-Wolfe methods for nonconvex optimization. Allerton Sashank J. Reddi, Suvrit Sra, Barnabás Póczos, Alexander J. Smola
2016	A*	`conf`	Stochastic Variance Reduction for Nonconvex Optimization. ICML Sashank J. Reddi, Ahmed Hefny, Suvrit Sra, Barnabás Póczos, Alexander J. Smola
2016	J	`jnl`	Stochastic Variance Reduction for Nonconvex Optimization. CoRR Sashank J. Reddi, Ahmed Hefny, Suvrit Sra, Barnabás Póczos, Alexander J. Smola
2016	J	`jnl`	Trend Filtering on Graphs. J. Mach. Learn. Res. Yu-Xiang Wang, James Sharpnack, Alexander J. Smola, Ryan J. Tibshirani
2016	A	`conf`	Using Navigation to Improve Recommendations in Real-Time. RecSys Chao-Yuan Wu, Christopher V. Alvino, Alexander J. Smola, Justin Basilico
2016	—	`conf`	Variance Reduction in Stochastic Gradient Langevin Dynamics. NIPS Kumar Avinava Dubey, Sashank J. Reddi, Sinead A. Williamson, Barnabás Póczos, Alexander J. Smola, Eric P. Xing
2015	A	`conf`	A la Carte - Learning Fast Kernels. AISTATS Zichao Yang, Andrew Gordon Wilson, Alexander J. Smola, Le Song
2015	A*	`conf`	ACCAMS: Additive Co-Clustering to Approximate Matrices Succinctly. WWW Alex Beutel, Amr Ahmed, Alexander J. Smola
2015	J	`jnl`	ACCAMS: Additive Co-Clustering to Approximate Matrices Succinctly. CoRR Alex Beutel, Amr Ahmed, Alexander J. Smola
2015	J	`jnl`	AdaDelay: Delay Adaptive Distributed Stochastic Convex Optimization. CoRR Suvrit Sra, Adams Wei Yu, Mu Li, Alexander J. Smola
2015	A*	`conf`	Annotating Needles in the Haystack without Looking: Product Information Extraction from Emails. KDD Weinan Zhang, Amr Ahmed, Jie Yang, Vanja Josifovski, Alexander J. Smola
2015	A	`conf`	Communication Efficient Coresets for Empirical Loss Minimization. UAI Sashank J. Reddi, Barnabás Póczos, Alexander J. Smola
2015	A*	`conf`	Cuckoo Linear Algebra. KDD Li Zhou, David G. Andersen, Mu Li, Alexander J. Smola
2015	J	`jnl`	Data Driven Resource Allocation for Distributed Learning. CoRR Travis Dick, Mu Li, Venkata Krishna Pillutla, Colin White, Maria-Florina Balcan, Alexander J. Smola
2015	A*	`conf`	Deep Fried Convnets. ICCV Zichao Yang, Marcin Moczulski, Misha Denil, Nando de Freitas, Alexander J. Smola, Le Song, Ziyu Wang
2015	A*	`conf`	Dirichlet-Hawkes Processes with Applications to Clustering Continuous-Time Document Streams. KDD Nan Du, Mehrdad Farajtabar, Amr Ahmed, Alexander J. Smola, Le Song
2015	A*	`conf`	Doubly Robust Covariate Shift Correction. AAAI Sashank Jakkam Reddi, Barnabás Póczos, Alexander J. Smola
2015	J	`jnl`	Explaining reviews and ratings with PACO: Poisson Additive Co-Clustering. CoRR Chao-Yuan Wu, Alex Beutel, Amr Ahmed, Alexander J. Smola
2015	A	`conf`	Fast Differentially Private Matrix Factorization. RecSys Ziqi Liu, Yu-Xiang Wang, Alexander J. Smola
2015	J	`jnl`	Fast Differentially Private Matrix Factorization. CoRR Ziqi Liu, Yu-Xiang Wang, Alexander J. Smola
2015	A*	`conf`	Fast Kronecker Inference in Gaussian Processes with non-Gaussian Likelihoods. ICML Seth R. Flaxman, Andrew Gordon Wilson, Daniel B. Neill, Hannes Nickisch, Alexander J. Smola
2015	—	`conf`	Fast and Guaranteed Tensor Decomposition via Sketching. NIPS Yining Wang, Hsiao-Yu Fish Tung, Alexander J. Smola, Anima Anandkumar
2015	J	`jnl`	Fast and Guaranteed Tensor Decomposition via Sketching. CoRR Yining Wang, Hsiao-Yu Fish Tung, Alexander J. Smola, Animashree Anandkumar
2015	J	`jnl`	Graph Partitioning via Parallel Submodular Approximation to Accelerate Distributed Machine Learning. CoRR Mu Li, Dave G. Andersen, Alexander J. Smola
2015	A	`conf`	Inferring Movement Trajectories from GPS Snippets. WSDM Mu Li, Amr Ahmed, Alexander J. Smola
2015	—	`conf`	On Variance Reduction in Stochastic Gradient Descent and its Asynchronous Variants. NIPS Sashank J. Reddi, Ahmed Hefny, Suvrit Sra, Barnabás Póczos, Alexander J. Smola
2015	J	`jnl`	On Variance Reduction in Stochastic Gradient Descent and its Asynchronous Variants. CoRR Sashank J. Reddi, Ahmed Hefny, Suvrit Sra, Barnabás Póczos, Alexander J. Smola
2015	A	`conf`	Preferential Attachment in Graphs with Affinities. AISTATS Jay Lee, Manzil Zaheer, Stephan Günnemann, Alexander J. Smola
2015	A*	`conf`	Privacy for Free: Posterior Sampling and Stochastic Gradient Monte Carlo. ICML Yu-Xiang Wang, Stephen E. Fienberg, Alexander J. Smola
2015	J	`jnl`	Privacy for Free: Posterior Sampling and Stochastic Gradient Monte Carlo. CoRR Yu-Xiang Wang, Stephen E. Fienberg, Alexander J. Smola
2015	J	`jnl`	Stacked Attention Networks for Image Question Answering. CoRR Zichao Yang, Xiaodong He, Jianfeng Gao, Li Deng, Alexander J. Smola
2015	A	`conf`	Trend Filtering on Graphs. AISTATS Yu-Xiang Wang, James Sharpnack, Alexander J. Smola, Ryan J. Tibshirani
2015	A*	`conf`	Who Supported Obama in 2012?: Ecological Inference through Distribution Regression. KDD Seth R. Flaxman, Yu-Xiang Wang, Alexander J. Smola
2014	J	`jnl`	A la Carte - Learning Fast Kernels. CoRR Zichao Yang, Alexander J. Smola, Le Song, Andrew Gordon Wilson
2014	A*	`conf`	CoBaFi: collaborative bayesian filtering. WWW Alex Beutel, Kenton Murray, Christos Faloutsos, Alexander J. Smola
2014	—	`conf`	Communication Efficient Distributed Machine Learning with the Parameter Server. NIPS Mu Li, David G. Andersen, Alexander J. Smola, Kai Yu
2014	J	`jnl`	Deep Fried Convnets. CoRR Zichao Yang, Marcin Moczulski, Misha Denil, Nando de Freitas, Alexander J. Smola, Le Song, Ziyu Wang
2014	A*	`conf`	Efficient mini-batch training for stochastic optimization. KDD Mu Li, Tong Zhang, Yuqiang Chen, Alexander J. Smola
2014	A*	`conf`	Jointly modeling aspects, ratings and sentiments for movie recommendation (JMARS). KDD Qiming Diao, Minghui Qiu, Chao-Yuan Wu, Alexander J. Smola, Jing Jiang, Chong Wang
2014	A*	`conf`	Randomized Nonlinear Component Analysis. ICML David Lopez-Paz, Suvrit Sra, Alexander J. Smola, Zoubin Ghahramani, Bernhard Schölkopf
2014	J	`jnl`	Randomized Nonlinear Component Analysis. CoRR David Lopez-Paz, Suvrit Sra, Alexander J. Smola, Zoubin Ghahramani, Bernhard Schölkopf
2014	A*	`conf`	Reducing the sampling complexity of topic models. KDD Aaron Q. Li, Amr Ahmed, Sujith Ravi, Alexander J. Smola
2014	A	`conf`	Scalable hierarchical multitask learning algorithms for conversion optimization in display advertising. WSDM Amr Ahmed, Abhimanyu Das, Alexander J. Smola
2014	A*	`conf`	Scaling Distributed Machine Learning with the Parameter Server. OSDI Mu Li, David G. Andersen, Jun Woo Park, Alexander J. Smola, Amr Ahmed, Vanja Josifovski, James Long, Eugene J. Shekita, Bor-Yiing Su
2014	—	`conf`	Spectral Methods for Indian Buffet Process Inference. NIPS Hsiao-Yu Fish Tung, Alexander J. Smola
2014	A	`conf`	Taxonomy discovery for personalized recommendation. WSDM Yuchen Zhang, Amr Ahmed, Vanja Josifovski, Alexander J. Smola
2014	A*	`conf`	The Falling Factorial Basis and Its Statistical Applications. ICML Yu-Xiang Wang, Alexander J. Smola, Ryan J. Tibshirani
2014	J	`jnl`	Trend Filtering on Graphs. CoRR Yu-Xiang Wang, James Sharpnack, Alexander J. Smola, Ryan J. Tibshirani
2013	A*	`conf`	Distributed large-scale natural graph factorization. WWW Amr Ahmed, Nino Shervashidze, Shravan M. Narayanamurthy, Vanja Josifovski, Alexander J. Smola
2013	—	`conf`	Fastfood - Computing Hilbert Space Expansions in loglinear time. ICML (3) Quoc V. Le, Tamás Sarlós, Alexander J. Smola
2013	A*	`conf`	Hierarchical geographical modeling of user locations from social media posts. WWW Amr Ahmed, Liangjie Hong, Alexander J. Smola
2013	A	`conf`	Instant foodie: predicting expert ratings from grassroots. CIKM Chenhao Tan, Ed H. Chi, David A. Huffaker, Gueorgi Kossinets, Alexander J. Smola
2013	A*	`conf`	Measurement and modeling of eye-mouse behavior in the presence of nonlinear page layouts. WWW Vidhya Navalpakkam, LaDawn Jentzsch, Rory Sayres, Sujith Ravi, Amr Ahmed, Alexander J. Smola
2013	—	`conf`	Nested Chinese Restaurant Franchise Process: Applications to User Tracking and Document Modeling. ICML (3) Amr Ahmed, Liangjie Hong, Alexander J. Smola
2013	A*	`conf`	The dataminer's guide to scalable mixed-membership and nonparametric bayesian models. KDD Amr Ahmed, Alexander J. Smola
2013	—	`conf`	Variance Reduction for Stochastic Gradient Optimization. NIPS Chong Wang, Xi Chen, Alexander J. Smola, Eric P. Xing
2012	J	`jnl`	A Kernel Two-Sample Test. J. Mach. Learn. Res. Arthur Gretton, Karsten M. Borgwardt, Malte J. Rasch, Bernhard Schölkopf, Alexander J. Smola
2012	A*	`conf`	Discovering geographical topics in the twitter stream. WWW Liangjie Hong, Amr Ahmed, Siva Gurumurthy, Alexander J. Smola, Kostas Tsioutsiouliklis
2012	J	`jnl`	Exponential Families for Conditional Random Fields CoRR Yasemin Altun, Alexander J. Smola, Thomas Hofmann
2012	A*	`conf`	Exponential Regret Bounds for Gaussian Process Bandits with Deterministic Observations. ICML Nando de Freitas, Alexander J. Smola, Masrour Zoghi
2012	A	`conf`	Fair and balanced: learning to present news stories. WSDM Amr Ahmed, Choon Hui Teo, S. V. N. Vishwanathan, Alexander J. Smola
2012	—	`conf`	FastEx: Hash Clustering with Exponential Families. NIPS Amr Ahmed, Sujith Ravi, Shravan M. Narayanamurthy, Alexander J. Smola
2012	J	`jnl`	Feature Selection via Dependence Maximization. J. Mach. Learn. Res. Le Song, Alexander J. Smola, Arthur Gretton, Justin Bedo, Karsten M. Borgwardt
2012	A*	`conf`	Friend or frenemy?: predicting signed ties in social networks. SIGIR Shuang-Hong Yang, Alexander J. Smola, Bo Long, Hongyuan Zha, Yi Chang
2012	J	`jnl`	Hokusai - Sketching Streams in Real Time CoRR Sergiy Matusevych, Alexander J. Smola, Amr Ahmed
2012	A	`conf`	Hokusai - Sketching Streams in Real Time. UAI Sergiy Matusevych, Alexander J. Smola, Amr Ahmed
2012	—	`conf`	Learning Networks of Heterogeneous Influence. NIPS Nan Du, Le Song, Alexander J. Smola, Ming Yuan
2012	A*	`conf`	Linear support vector machines via dual cached loops. KDD Shin Matsushima, S. V. N. Vishwanathan, Alexander J. Smola
2012	J	`jnl`	Regret Bounds for Deterministic Gaussian Process Bandits CoRR Nando de Freitas, Alexander J. Smola, Masrour Zoghi
2012	A	`conf`	Scalable inference in latent variable models. WSDM Amr Ahmed, Mohamed Aly, Joseph Gonzalez, Shravan M. Narayanamurthy, Alexander J. Smola
2012	J	`jnl`	Super-Samples from Kernel Herding CoRR Yutian Chen, Max Welling, Alexander J. Smola
2012	A	`conf`	Web-scale multi-task feature selection for behavioral targeting. CIKM Amr Ahmed, Mohamed Aly, Abhimanyu Das, Alexander J. Smola, Tasos Anastasakos
2011	A	`conf`	Bid generation for advanced match in sponsored search. WSDM Andrei Z. Broder, Evgeniy Gabrilovich, Vanja Josifovski, George Mavromatis, Alexander J. Smola
2011	A*	`conf`	Collaborative competitive filtering: learning recommender using context of user choice. SIGIR Shuang-Hong Yang, Bo Long, Alexander J. Smola, Hongyuan Zha, Zhaohui Zheng
2011	J	`jnl`	Guest editorial: model selection and optimization in machine learning. Mach. Learn. Süreyya Özögür-Akyüz, Devrim Ünay, Alexander J. Smola
2011	J	`jnl`	Human Action Segmentation and Recognition Using Discriminative Semi-Markov Models. Int. J. Comput. Vis. Qinfeng Shi, Li Cheng, Li Wang, Alexander J. Smola
2011	A*	`conf`	Like like alike: joint friendship and interest propagation in social networks. WWW Shuang-Hong Yang, Bo Long, Alexander J. Smola, Narayanan Sadagopan, Zhaohui Zheng, Hongyuan Zha
2011	A	`conf`	Linear-Time Estimators for Propensity Scores. AISTATS Deepak Agarwal, Lihong Li, Alexander J. Smola
2011	A*	`conf`	Multiple domain user personalization. KDD Yucheng Low, Deepak Agarwal, Alexander J. Smola
2011	A	`conf`	Online Inference for the Infinite Topic-Cluster Model: Storylines from Streaming Text. AISTATS Amr Ahmed, Qirong Ho, Choon Hui Teo, Jacob Eisenstein, Alexander J. Smola, Eric P. Xing
2011	J	`jnl`	Parallel Online Learning CoRR Daniel J. Hsu, Nikos Karampatziakis, John Langford, Alexander J. Smola
2011	A	`conf`	Scalable clustering of news search results. WSDM Srinivas Vadrevu, Choon Hui Teo, Suju Rajan, Kunal Punera, Byron Dom, Alexander J. Smola, Yi Chang, Zhaohui Zheng
2011	A*	`conf`	Scalable distributed inference of dynamic user interests for behavioral targeting. KDD Amr Ahmed, Yucheng Low, Mohamed Aly, Vanja Josifovski, Alexander J. Smola
2011	A*	`conf`	Unified analysis of streaming news. WWW Amr Ahmed, Qirong Ho, Jacob Eisenstein, Eric P. Xing, Alexander J. Smola, Choon Hui Teo
2011	—	`conf`	WWW 2011 invited tutorial overview: latent variable models on the internet. WWW (Companion Volume) Amr Ahmed, Alexander J. Smola
2010	J	`jnl`	An Architecture for Parallel Topic Models. Proc. VLDB Endow. Alexander J. Smola, Shravan M. Narayanamurthy
2010	J	`jnl`	Bundle Methods for Regularized Risk Minimization. J. Mach. Learn. Res. Choon Hui Teo, S. V. N. Vishwanathan, Alexander J. Smola, Quoc V. Le
2010	A	`conf`	Collaborative Filtering on a Budget. AISTATS Alexandros Karatzoglou, Alexander J. Smola, Markus Weimer
2010	J	`jnl`	Discriminative frequent subgraph mining with optimality guarantees. Stat. Anal. Data Min. Marisa Thoma, Hong Cheng, Arthur Gretton, Jiawei Han, Hans-Peter Kriegel, Alexander J. Smola, Le Song, Philip S. Yu, Xifeng Yan, Karsten M. Borgwardt
2010	—	`conf`	Distributed Flow Algorithms for Scalable Similarity Visualization. ICDM Workshops Novi Quadrianto, Dale Schuurmans, Alexander J. Smola
2010	A*	`conf`	Hilbert Space Embeddings of Hidden Markov Models. ICML Le Song, Byron Boots, Sajid M. Siddiqi, Geoffrey J. Gordon, Alexander J. Smola
2010	A	`conf`	IntervalRank: isotonic regression with listwise and pairwise constraints. WSDM Taesup Moon, Alexander J. Smola, Yi Chang, Zhaohui Zheng
2010	J	`jnl`	Kernelized Sorting. IEEE Trans. Pattern Anal. Mach. Intell. Novi Quadrianto, Alexander J. Smola, Le Song, Tinne Tuytelaars
2010	—	`conf`	Multitask Learning without Label Correspondences. NIPS Novi Quadrianto, Alexander J. Smola, Tibério S. Caetano, S. V. N. Vishwanathan, James Petterson
2010	—	`conf`	Optimal Web-Scale Tiering as a Flow Problem. NIPS Gilbert Leung, Novi Quadrianto, Alexander J. Smola, Kostas Tsioutsiouliklis
2010	—	`conf`	Parallelized Stochastic Gradient Descent. NIPS Martin Zinkevich, Markus Weimer, Alexander J. Smola, Lihong Li
2010	A	`conf`	Super-Samples from Kernel Herding. UAI Yutian Chen, Max Welling, Alexander J. Smola
2010	J	`jnl`	Wearable sensor activity analysis using semi-Markov models with a grammar. Pervasive Mob. Comput. Owen Thomas, Peter Sunehag, Gideon Dror, Sungrack Yun, Sungwoong Kim, Matthew W. Robards, Alexander J. Smola, Daniel Green, Philo Saunders
2010	—	`conf`	Word Features for Latent Dirichlet Allocation. NIPS James Petterson, Alexander J. Smola, Tibério S. Caetano, Wray L. Buntine, Shravan M. Narayanamurthy
2009	—	`conf`	Distribution Matching for Transduction. NIPS Novi Quadrianto, James Petterson, Alexander J. Smola
2009	J	`jnl`	Estimating Labels from Label Proportions. J. Mach. Learn. Res. Novi Quadrianto, Alexander J. Smola, Tibério S. Caetano, Quoc V. Le
2009	J	`jnl`	Feature Hashing for Large Scale Multitask Learning CoRR Kilian Q. Weinberger, Anirban Dasgupta, Josh Attenberg, John Langford, Alexander J. Smola
2009	A*	`conf`	Feature hashing for large scale multitask learning. ICML Kilian Q. Weinberger, Anirban Dasgupta, John Langford, Alexander J. Smola, Josh Attenberg
2009	J	`jnl`	Hash Kernels for Structured Data. J. Mach. Learn. Res. Qinfeng Shi, James Petterson, Gideon Dror, John Langford, Alexander J. Smola, S. V. N. Vishwanathan
2009	A	`conf`	Hash Kernels. AISTATS Qinfeng Shi, James Petterson, Gideon Dror, John Langford, Alexander J. Smola, Alexander L. Strehl, Vishy Vishwanathan
2009	A*	`conf`	Hilbert space embeddings of conditional distributions with applications to dynamical systems. ICML Le Song, Jonathan Huang, Alexander J. Smola, Kenji Fukumizu
2009	J	`jnl`	Learning Graph Matching. IEEE Trans. Pattern Anal. Mach. Intell. Tibério S. Caetano, Julian J. McAuley, Li Cheng, Quoc V. Le, Alexander J. Smola
2009	A	`conf`	Near-optimal Supervised Feature Selection among Frequent Subgraphs. SDM Marisa Thoma, Hong Cheng, Arthur Gretton, Jiawei Han, Hans-Peter Kriegel, Alexander J. Smola, Le Song, Philip S. Yu, Xifeng Yan, Karsten M. Borgwardt
2009	A	`conf`	Relative Novelty Detection. AISTATS Alexander J. Smola, Le Song, Choon Hui Teo
2009	—	`conf`	Slow Learners are Fast. NIPS Martin Zinkevich, Alexander J. Smola, John Langford
2008	J	`jnl`	A Kernel Method for the Two-Sample Problem CoRR Arthur Gretton, Karsten M. Borgwardt, Malte J. Rasch, Bernhard Schölkopf, Alexander J. Smola
2008	A	`conf`	Adaptive collaborative filtering. RecSys Markus Weimer, Alexandros Karatzoglou, Alexander J. Smola
2008	A*	`conf`	Discriminative human action segmentation and recognition using semi-Markov model. CVPR Qinfeng Shi, Li Wang, Li Cheng, Alexander J. Smola
2008	A*	`conf`	Estimating labels from label proportions. ICML Novi Quadrianto, Alexander J. Smola, Tibério S. Caetano, Quoc V. Le
2008	—	`conf`	Improving Maximum Margin Matrix Factorization. ECML/PKDD (1) Markus Weimer, Alexandros Karatzoglou, Alexander J. Smola
2008	J	`jnl`	Improving maximum margin matrix factorization. Mach. Learn. Markus Weimer, Alexandros Karatzoglou, Alexander J. Smola
2008	—	`conf`	Kernel Measures of Independence for non-iid Data. NIPS Xinhua Zhang, Le Song, Arthur Gretton, Alexander J. Smola
2008	—	`conf`	Kernelized Sorting. NIPS Novi Quadrianto, Le Song, Alexander J. Smola
2008	J	`jnl`	Learning Graph Matching CoRR Tibério S. Caetano, Julian J. McAuley, Li Cheng, Quoc V. Le, Alexander J. Smola
2008	—	`conf`	Performance Evaluation of the NVIDIA GeForce 8800 GTX GPU for Machine Learning. ICCS (1) Ahmed H. El Zein, Eric McCreath, Alistair P. Rendell, Alexander J. Smola
2008	J	`jnl`	Robust Near-Isometric Matching via Structured Learning of Graphical Models CoRR Julian J. McAuley, Tibério S. Caetano, Alexander J. Smola
2008	—	`conf`	Robust Near-Isometric Matching via Structured Learning of Graphical Models. NIPS Julian J. McAuley, Tibério S. Caetano, Alexander J. Smola
2008	A*	`conf`	Tailoring density estimation via reproducing kernel moment matching. ICML Le Song, Xinhua Zhang, Alexander J. Smola, Arthur Gretton, Bernhard Schölkopf
2008	—	`conf`	Tighter Bounds for Structured Estimation. NIPS Olivier Chapelle, Chuong B. Do, Quoc V. Le, Alexander J. Smola, Choon Hui Teo
2007	B	`conf`	A Hilbert Space Embedding for Distributions. ALT Alexander J. Smola, Arthur Gretton, Le Song, Bernhard Schölkopf
2007	B	`conf`	A Hilbert Space Embedding for Distributions. Discovery Science Alexander J. Smola, Arthur Gretton, Le Song, Bernhard Schölkopf
2007	A*	`conf`	A Kernel Approach to Comparing Distributions. AAAI Arthur Gretton, Karsten M. Borgwardt, Malte J. Rasch, Bernhard Schölkopf, Alexander J. Smola
2007	—	`conf`	A Kernel Statistical Test of Independence. NIPS Arthur Gretton, Kenji Fukumizu, Choon Hui Teo, Le Song, Bernhard Schölkopf, Alexander J. Smola
2007	A*	`conf`	A dependence maximization view of clustering. ICML Le Song, Alexander J. Smola, Arthur Gretton, Karsten M. Borgwardt
2007	A*	`conf`	A scalable modular convex solver for regularized risk minimization. KDD Choon Hui Teo, Alexander J. Smola, S. V. N. Vishwanathan, Quoc V. Le
2007	J	`jnl`	Binet-Cauchy Kernels on Dynamical Systems and its Application to the Analysis of Dynamic Scenes. Int. J. Comput. Vis. S. V. N. Vishwanathan, Alexander J. Smola, René Vidal
2007	—	`conf`	Bundle Methods for Machine Learning. NIPS Alexander J. Smola, S. V. N. Vishwanathan, Quoc V. Le
2007	—	`conf`	COFI RANK - Maximum Margin Matrix Factorization for Collaborative Ranking . NIPS Markus Weimer, Alexandros Karatzoglou, Quoc V. Le, Alexander J. Smola
2007	—	`conf`	Colored Maximum Variance Unfolding. NIPS Le Song, Alexander J. Smola, Karsten M. Borgwardt, Arthur Gretton
2007	—	`conf`	Convex Learning with Invariances. NIPS Choon Hui Teo, Amir Globerson, Sam T. Roweis, Alexander J. Smola
2007	J	`jnl`	Direct Optimization of Ranking Measures CoRR Quoc V. Le, Alexander J. Smola
2007	—	`conf`	Gene selection via the BAHSIC family of algorithms. ISMB/ECCB (Supplement of Bioinformatics) Le Song, Justin Bedo, Karsten M. Borgwardt, Arthur Gretton, Alexander J. Smola
2007	A*	`conf`	Learning Graph Matching. ICCV Tibério S. Caetano, Li Cheng, Quoc V. Le, Alexander J. Smola
2007	—	`conf`	Learning Graph Matching. MLG Alexander J. Smola
2007	—	`conf`	Semi-Markov Models for Sequence Segmentation. EMNLP-CoNLL Qinfeng Shi, Yasemin Altun, Alexander J. Smola, S. V. N. Vishwanathan
2007	J	`jnl`	Supervised Feature Selection via Dependence Estimation CoRR Le Song, Alexander J. Smola, Arthur Gretton, Karsten M. Borgwardt, Justin Bedo
2007	A*	`conf`	Supervised feature selection via dependence estimation. ICML Le Song, Alexander J. Smola, Arthur Gretton, Karsten M. Borgwardt, Justin Bedo
2007	J	`jnl`	The Need for Open Source Software in Machine Learning. J. Mach. Learn. Res. Sören Sonnenburg, Mikio L. Braun, Cheng Soon Ong, Samy Bengio, Léon Bottou, Geoffrey Holmes, Yann LeCun, Klaus-Robert Müller, Fernando Pereira, Carl Edward Rasmussen, Gunnar Rätsch, Bernhard Schölkopf, Alexander J. Smola, Pascal Vincent, Jason Weston, Robert C. Williamson
2006	—	`conf`	A Kernel Method for the Two-Sample-Problem. NIPS Arthur Gretton, Karsten M. Borgwardt, Malte J. Rasch, Bernhard Schölkopf, Alexander J. Smola
2006	—	`conf`	Correcting Sample Selection Bias by Unlabeled Data. NIPS Jiayuan Huang, Alexander J. Smola, Arthur Gretton, Karsten M. Borgwardt, Bernhard Schölkopf
2006	—	`conf`	Integrating structured biological data by Kernel Maximum Mean Discrepancy. ISMB (Supplement of Bioinformatics) Karsten M. Borgwardt, Arthur Gretton, Malte J. Rasch, Hans-Peter Kriegel, Bernhard Schölkopf, Alexander J. Smola
2006	J	`jnl`	Kernel extrapolation. Neurocomputing S. V. N. Vishwanathan, Karsten M. Borgwardt, Omri Guttman, Alexander J. Smola
2006	J	`jnl`	Kernel methods and the exponential family. Neurocomputing Stéphane Canu, Alexander J. Smola
2006	A*	`conf`	Learning high-order MRF priors of color images. ICML Julian J. McAuley, Tibério S. Caetano, Alexander J. Smola, Matthias O. Franz
2006	—	`conf`	Newton-Like Methods for Nonparametric Independent Component Analysis. ICONIP (1) Hao Shen, Knut Hüper, Alexander J. Smola
2006	J	`jnl`	Nonparametric Quantile Estimation. J. Mach. Learn. Res. Ichiro Takeuchi, Quoc V. Le, Tim D. Sears, Alexander J. Smola
2006	J	`jnl`	Second Order Cone Programming Approaches for Handling Missing and Uncertain Data. J. Mach. Learn. Res. Pannagadatta K. Shivaswamy, Chiranjib Bhattacharyya, Alexander J. Smola
2006	A*	`conf`	Simpler knowledge-based support vector machines. ICML Quoc V. Le, Alexander J. Smola, Thomas Gärtner
2006	J	`jnl`	Step Size Adaptation in Reproducing Kernel Hilbert Space. J. Mach. Learn. Res. S. V. N. Vishwanathan, Nicol N. Schraudolph, Alexander J. Smola
2006	—	`conf`	Transductive Gaussian Process Regression with Automatic Model Selection. ECML Quoc V. Le, Alexander J. Smola, Thomas Gärtner, Yasemin Altun
2006	A*	`conf`	Unifying Divergence Minimization and Statistical Inference Via Convex Duality. COLT Yasemin Altun, Alexander J. Smola
2005	J	`jnl`	Boîte à outils SVM simple et rapide. Rev. d'Intelligence Artif. Gaëlle Loosli, Stéphane Canu, S. V. N. Vishwanathan, Alexander J. Smola, M. Chattopadhyay
2005	J	`jnl`	Experimentally optimal nu in support vector regression for different noise models and parameter settings. Neural Networks Athanassia Chalimourda, Bernhard Schölkopf, Alexander J. Smola
2005	A*	`conf`	Heteroscedastic Gaussian process regression. ICML Quoc V. Le, Alexander J. Smola, Stéphane Canu
2005	B	`conf`	Joint Regularization. ESANN Karsten M. Borgwardt, Omri Guttman, S. V. N. Vishwanathan, Alexander J. Smola
2005	A	`conf`	Kernel Constrained Covariance for Dependence Measurement. AISTATS Arthur Gretton, Alexander J. Smola, Olivier Bousquet, Ralf Herbrich, Andrei Belitski, Mark Augath, Yusuke Murayama, Jon Pauls, Bernhard Schölkopf, Nikos K. Logothetis
2005	J	`jnl`	Kernel Methods for Measuring Independence. J. Mach. Learn. Res. Arthur Gretton, Ralf Herbrich, Alexander J. Smola, Olivier Bousquet, Bernhard Schölkopf
2005	A	`conf`	Kernel Methods for Missing Variables. AISTATS Alexander J. Smola, S. V. N. Vishwanathan, Thomas Hofmann
2005	B	`conf`	Kernel methods and the exponential family. ESANN Stéphane Canu, Alexander J. Smola
2005	—	`conf`	Large-Scale Multiclass Transduction. NIPS Thomas Gärtner, Quoc V. Le, Simon Burton, Alexander J. Smola, S. V. N. Vishwanathan
2005	J	`jnl`	Learning the Kernel with Hyperkernels. J. Mach. Learn. Res. Cheng Soon Ong, Alexander J. Smola, Robert C. Williamson
2005	B	`conf`	Measuring Statistical Dependence with Hilbert-Schmidt Norms. ALT Arthur Gretton, Olivier Bousquet, Alexander J. Smola, Bernhard Schölkopf
2005	—	`conf`	Parametric model-based clustering. Data Mining, Intrusion Detection, Information Assurance, and Data Networks Security Vladimir Nikulin, Alexander J. Smola
2005	—	`conf`	Protein function prediction via graph kernels. ISMB (Supplement of Bioinformatics) Karsten M. Borgwardt, Cheng Soon Ong, Stefan Schönauer, S. V. N. Vishwanathan, Alexander J. Smola, Hans-Peter Kriegel
2005	—	`conf`	Step size-adapted online support vector learning. ISSPA Alexandros Karatzoglou, S. V. N. Vishwanathan, Nicol N. Schraudolph, Alexander J. Smola
2005	—	`conf`	Universal Clustering with Regularization in Probabilistic Space. MLDM Vladimir Nikulin, Alexander J. Smola
2004	—	`conf`	A Second Order Cone programming Formulation for Classifying Missing Data. NIPS Chiranjib Bhattacharyya, Pannagadatta K. Shivaswamy, Alexander J. Smola
2004	J	`jnl`	A tutorial on support vector regression. Stat. Comput. Alexander J. Smola, Bernhard Schölkopf
2004	—	`conf`	Binet-Cauchy Kernels. NIPS S. V. N. Vishwanathan, Alexander J. Smola
2004	J	`jnl`	Experimentally optimal v in support vector regression for different noise models and parameter settings. Neural Networks Athanassia Chalimourda, Bernhard Schölkopf, Alexander J. Smola
2004	A	`conf`	Exponential Families for Conditional Random Fields. UAI Yasemin Altun, Alexander J. Smola, Thomas Hofmann
2004	A*	`conf`	Gaussian process classification for segmenting and annotating sequences. ICML Yasemin Altun, Thomas Hofmann, Alexander J. Smola
2004	A*	`conf`	Learning with non-positive kernels. ICML Cheng Soon Ong, Xavier Mary, Stéphane Canu, Alexander J. Smola
2004	J	`jnl`	Online learning with kernels. IEEE Trans. Signal Process. Jyrki Kivinen, Alexander J. Smola, Robert C. Williamson
2003	—	`ed.`	Advanced Lectures on Machine Learning, Machine Learning Summer School 2002, Canberra, Australia, February 11-22, 2002, Revised Lectures Machine Learning Summer School Shahar Mendelson, Alexander J. Smola
2003	J	`jnl`	Classification in a normalized feature space using support vector machines. IEEE Trans. Neural Networks Arnulf B. A. Graf, Alexander J. Smola, Silvio Borer
2003	J	`jnl`	Constructing Descriptive and Discriminative Nonlinear Features: Rayleigh Coefficients in Kernel Feature Spaces. IEEE Trans. Pattern Anal. Mach. Intell. Sebastian Mika, Gunnar Rätsch, Jason Weston, Bernhard Schölkopf, Alexander J. Smola, Klaus-Robert Müller
2003	A*	`conf`	Kernels and Regularization on Graphs. COLT Alexander J. Smola, Risi Kondor
2003	—	`conf`	Laplace Propagation. NIPS Alexander J. Smola, Vishy Vishwanathan, Eleazar Eskin
2003	A*	`conf`	Machine Learning with Hyperkernels. ICML Cheng Soon Ong, Alexander J. Smola
2003	A*	`conf`	SimpleSVM. ICML S. V. N. Vishwanathan, Alexander J. Smola, M. Narasimha Murty
2003	—	`conf`	The kernel mutual information. ICASSP (4) Arthur Gretton, Ralf Herbrich, Alexander J. Smola
2002	—	`conf`	A Short Introduction to Learning with Kernels. Machine Learning Summer School Bernhard Schölkopf, Alexander J. Smola
2002	—	`conf`	Adapting Codes and Embeddings for Polychotomies. NIPS Gunnar Rätsch, Alexander J. Smola, Sebastian Mika
2002	—	`conf`	Bayesian Kernel Methods. Machine Learning Summer School Alexander J. Smola, Bernhard Schölkopf
2002	—	`conf`	Fast Kernels for String and Tree Matching. NIPS S. V. N. Vishwanathan, Alexander J. Smola
2002	—	`conf`	Hyperkernels. NIPS Cheng Soon Ong, Alexander J. Smola, Robert C. Williamson
2002	B	`conf`	Large Margin Classification for Moving Targets. ALT Jyrki Kivinen, Alexander J. Smola, Robert C. Williamson
2002	J	`jnl`	Minimal Kernel Classifiers. J. Mach. Learn. Res. Glenn Fung, Olvi L. Mangasarian, Alexander J. Smola
2002	A*	`conf`	Multi-Instance Kernels. ICML Thomas Gärtner, Peter A. Flach, Adam Kowalczyk, Alexander J. Smola
2001	—	`conf`	A Generalized Representer Theorem. COLT/EuroCOLT Bernhard Schölkopf, Ralf Herbrich, Alexander J. Smola
2001	A	`conf`	An improved training algorithm for kernel Fisher discriminants. AISTATS Sebastian Mika, Alexander J. Smola, Bernhard Schölkopf
2001	J	`jnl`	Estimating the Support of a High-Dimensional Distribution. Neural Comput. Bernhard Schölkopf, John C. Platt, John Shawe-Taylor, Alexander J. Smola, Robert C. Williamson
2001	J	`jnl`	Generalization performance of regularization networks and support vector machines via entropy numbers of compact operators. IEEE Trans. Inf. Theory Robert C. Williamson, Alexander J. Smola, Bernhard Schölkopf
2001	—	`conf`	Kernel Machines and Boolean Functions. NIPS Adam Kowalczyk, Alexander J. Smola, Robert C. Williamson
2001	—	`conf`	Online Learning with Kernels. NIPS Jyrki Kivinen, Alexander J. Smola, Robert C. Williamson
2001	J	`jnl`	Regularized Principal Manifolds. J. Mach. Learn. Res. Alexander J. Smola, Sebastian Mika, Bernhard Schölkopf, Robert C. Williamson
2000	—	`conf`	Choosing in Support Vector Regression with Different Noise Models: Theory and Experiments. IJCNN (5) Athanassia Chalimourda, Bernhard Schölkopf, Alexander J. Smola
2000	A*	`conf`	Entropy Numbers of Linear Function Classes. COLT Robert C. Williamson, Alexander J. Smola, Bernhard Schölkopf
2000	J	`jnl`	New Support Vector Algorithms. Neural Comput. Bernhard Schölkopf, Alexander J. Smola, Robert C. Williamson, Peter L. Bartlett
2000	A*	`conf`	Query Learning with Large Margin Classifiers. ICML Colin Campbell, Nello Cristianini, Alexander J. Smola
2000	—	`conf`	Regularization with Dot-Product Kernels. NIPS Alexander J. Smola, Zoltán L. Óvári, Robert C. Williamson
2000	B	`conf`	Robust Ensemble Learning for Data Mining. PAKDD Gunnar Rätsch, Bernhard Schölkopf, Alexander J. Smola, Sebastian Mika, Takashi Onoda, Klaus-Robert Müller
2000	—	`conf`	Sparse Greedy Gaussian Process Regression. NIPS Alexander J. Smola, Peter L. Bartlett
2000	A*	`conf`	Sparse Greedy Matrix Approximation for Machine Learning. ICML Alexander J. Smola, Bernhard Schölkopf
1999	—	`conf`	Engineering Support Vector Machine Kerneis That Recognize Translation Initialion Sites. German Conference on Bioinformatics Alexander Zien, Gunnar Rätsch, Sebastian Mika, Bernhard Schölkopf, Christian Lemmen, Alexander J. Smola, Thomas Lengauer, Klaus-Robert Müller
1999	—	`conf`	Entropy Numbers, Operators and Support Vector Kernels. EuroCOLT Robert C. Williamson, Alexander J. Smola, Bernhard Schölkopf
1999	J	`jnl`	Input space versus feature space in kernel-based methods. IEEE Trans. Neural Networks Bernhard Schölkopf, Sebastian Mika, Christopher J. C. Burges, Phil Knirsch, Klaus-Robert Müller, Gunnar Rätsch, Alexander J. Smola
1999	—	`conf`	Invariant Feature Extraction and Classification in Kernel Spaces. NIPS Sebastian Mika, Gunnar Rätsch, Jason Weston, Bernhard Schölkopf, Alexander J. Smola, Klaus-Robert Müller
1999	J	`jnl`	Lernen mit Kernen: Support-Vektor-Methoden zur Analyse hochdimensionaler Daten. Inform. Forsch. Entwickl. Bernhard Schölkopf, Klaus-Robert Müller, Alexander J. Smola
1999	—	`conf`	Regularized Principal Manifolds. EuroCOLT Alexander J. Smola, Robert C. Williamson, Sebastian Mika, Bernhard Schölkopf
1999	—	`conf`	Support Vector Method for Novelty Detection. NIPS Bernhard Schölkopf, Robert C. Williamson, Alexander J. Smola, John Shawe-Taylor, John C. Platt
1999	—	`conf`	The Entropy Regularization Information Criterion. NIPS Alexander J. Smola, John Shawe-Taylor, Bernhard Schölkopf, Robert C. Williamson
1999	—	`conf`	v-Arc: Ensemble Learning in the Presence of Outliers. NIPS Gunnar Rätsch, Bernhard Schölkopf, Alexander J. Smola, Klaus-Robert Müller, Takashi Onoda, Sebastian Mika
1998	—	`conf`	Fast Approximation of Support Vector Kernel Expansions, and an Interpretation of Clustering as Approximation in Feature Spaces. DAGM-Symposium Bernhard Schölkopf, Alexander J. Smola, Phil Knirsch, Chris Burges
1998	—	`conf`	Kernel PCA and De-Noising in Feature Spaces. NIPS Sebastian Mika, Bernhard Schölkopf, Alexander J. Smola, Klaus-Robert Müller, Matthias Scholz, Gunnar Rätsch
1998	—	`—`	Learning with kernels. Alexander J. Smola
1998	J	`jnl`	Nonlinear Component Analysis as a Kernel Eigenvalue Problem. Neural Comput. Bernhard Schölkopf, Alexander J. Smola, Klaus-Robert Müller
1998	J	`jnl`	On a Kernel-Based Method for Pattern Recognition, Regression, Approximation, and Operator Inversion. Algorithmica Alexander J. Smola, Bernhard Schölkopf
1998	—	`conf`	Semiparametric Support Vector and Linear Programming Machines. NIPS Alexander J. Smola, Thilo-Thomas Frieß, Bernhard Schölkopf
1998	—	`conf`	Shrinking the Tube: A New Support Vector Regression Algorithm. NIPS Bernhard Schölkopf, Peter L. Bartlett, Alexander J. Smola, Robert C. Williamson
1998	J	`jnl`	The connection between regularization operators and support vector kernels. Neural Networks Alexander J. Smola, Bernhard Schölkopf, Klaus-Robert Müller
1997	—	`conf`	From Regularization Operators to Support Vector Kernels. NIPS Alexander J. Smola, Bernhard Schölkopf
1997	C	`conf`	Kernel Principal Component Analysis. ICANN Bernhard Schölkopf, Alexander J. Smola, Klaus-Robert Müller
1997	C	`conf`	Predicting Time Series with Support Vector Machines. ICANN Klaus-Robert Müller, Alexander J. Smola, Gunnar Rätsch, Bernhard Schölkopf, Jens Kohlmorgen, Vladimir Vapnik
1997	—	`conf`	Prior Knowledge in Support Vector Kernels. NIPS Bernhard Schölkopf, Patrice Y. Simard, Alexander J. Smola, Vladimir Vapnik
1996	—	`conf`	Support Vector Method for Function Approximation, Regression Estimation and Signal Processing. NIPS Vladimir Vapnik, Steven E. Golowich, Alexander J. Smola
1996	—	`conf`	Support Vector Regression Machines. NIPS Harris Drucker, Christopher J. C. Burges, Linda Kaufman, Alexander J. Smola, Vladimir Vapnik