Aurélien Lucchi

152 papers A* 36A 12B 2Journal 86Unranked 15

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	Adaptive Methods Are Preferable in High Privacy Settings: An SDE Perspective. CoRR Enea Monzio Compagnoni, Alessandro Stanghellini, Rustem Islamov, Aurélien Lucchi, Anastasiia Koloskova
2026	J	`jnl`	Byzantine-Robust and Differentially Private Federated Optimization under Weaker Assumptions. CoRR Rustem Islamov, Grigory Malinovsky, Alexander Gaponov, Aurélien Lucchi, Peter Richtárik, Eduard Gorbunov
2026	J	`jnl`	Multi-Task GRPO: Reliable LLM Reasoning Across Tasks. CoRR Shyam Sundhar Ramesh, Xiaotong Ji, Matthieu Zimmer, Sangwoong Yoon, Zhiyong Wang, Haitham Bou-Ammar, Aurélien Lucchi, Ilija Bogunovic
2026	J	`jnl`	On the Role of Batch Size in Stochastic Conditional Gradient Methods. CoRR Rustem Islamov, Roman Machacek, Aurélien Lucchi, Antonio Silveti-Falls, Eduard Gorbunov, Volkan Cevher
2026	J	`jnl`	Optimizer choice matters for the emergence of Neural Collapse. CoRR Jim Zhao, Tin Sum Cheng, Wojciech Masarczyk, Aurélien Lucchi
2025	A*	`conf`	Adaptive Methods through the Lens of SDEs: Theoretical Insights on the Role of Noise. ICLR Enea Monzio Compagnoni, Tianlin Liu, Rustem Islamov, Frank Norbert Proske, Antonio Orvieto, Aurélien Lucchi
2025	A	`conf`	Cubic regularized subspace Newton for non-convex optimization. AISTATS Jim Zhao, Nikita Doikov, Aurélien Lucchi
2025	J	`jnl`	Double Momentum and Error Feedback for Clipping with Fast Rates and Differential Privacy. CoRR Rustem Islamov, Samuel Horváth, Aurélien Lucchi, Peter Richtárik, Eduard Gorbunov
2025	J	`jnl`	Enhancing Optimizer Stability: Momentum Adaptation of The NGN Step-size. CoRR Rustem Islamov, Niccolò Ajroldi, Antonio Orvieto, Aurélien Lucchi
2025	J	`jnl`	Optimization Guarantees for Square-Root Natural-Gradient Variational Inference. CoRR Navish Kumar, Thomas Möllenhoff, Mohammad Emtiyaz Khan, Aurélien Lucchi
2025	J	`jnl`	Optimization Guarantees for Square-Root Natural-Gradient Variational Inference. Trans. Mach. Learn. Res. Navish Kumar, Thomas Möllenhoff, Mohammad Emtiyaz Khan, Aurélien Lucchi
2025	J	`jnl`	Sharp Generalization Bounds for Foundation Models with Asymmetric Randomized Low-Rank Adapters. CoRR Anastasis Kratsios, Tin Sum Cheng, Aurélien Lucchi, Haitz Sáez de Ocáriz Borde
2025	J	`jnl`	Trainability of Quantum Models Beyond Known Classical Simulability. CoRR Sabri Meyer, Francesco Scala, Francesco Tacchino, Aurélien Lucchi
2025	A	`conf`	Unbiased and Sign Compression in Distributed Learning: Comparing Noise Resilience via SDEs. AISTATS Enea Monzio Compagnoni, Rustem Islamov, Frank Norbert Proske, Aurélien Lucchi
2025	J	`jnl`	Unbiased and Sign Compression in Distributed Learning: Comparing Noise Resilience via SDEs. CoRR Enea Monzio Compagnoni, Rustem Islamov, Frank Norbert Proske, Aurélien Lucchi
2025	J	`jnl`	Unpacking Softmax: How Temperature Drives Representation Collapse, Compression, and Generalization. CoRR Wojciech Masarczyk, Mateusz Ostaszewski, Tin Sum Cheng, Tomasz Trzcinski, Aurélien Lucchi, Razvan Pascanu
2025	J	`jnl`	When the Left Foot Leads to the Right Path: Bridging Initial Prejudice and Trainability. CoRR Alberto Bassi, Carlo Albert, Aurélien Lucchi, Marco Baity-Jesi, Emanuele Francazi
2025	J	`jnl`	Where You Place the Norm Matters: From Prejudiced to Neutral Initializations. CoRR Emanuele Francazi, Francesco Pinto, Aurélien Lucchi, Marco Baity-Jesi
2025	J	`jnl`	Why Do We Need Warm-up? A Theoretical Perspective. CoRR Foivos Alimisis, Rustem Islamov, Aurélien Lucchi
2024	A*	`conf`	A Comprehensive Analysis on the Learning Curve in Kernel Ridge Regression. NeurIPS Tin Sum Cheng, Aurélien Lucchi, Anastasis Kratsios, David Belius
2024	J	`jnl`	A Comprehensive Analysis on the Learning Curve in Kernel Ridge Regression. CoRR Tin Sum Cheng, Aurélien Lucchi, Anastasis Kratsios, David Belius
2024	J	`jnl`	Adaptive Methods through the Lens of SDEs: Theoretical Insights on the Role of Noise. CoRR Enea Monzio Compagnoni, Tianlin Liu, Rustem Islamov, Frank Norbert Proske, Antonio Orvieto, Aurélien Lucchi
2024	A*	`conf`	Characterizing Overfitting in Kernel Ridgeless Regression Through the Eigenspectrum. ICML Tin Sum Cheng, Aurélien Lucchi, Anastasis Kratsios, David Belius
2024	J	`jnl`	Characterizing Overfitting in Kernel Ridgeless Regression Through the Eigenspectrum. CoRR Tin Sum Cheng, Aurélien Lucchi, Anastasis Kratsios, David Belius
2024	J	`jnl`	Cubic regularized subspace Newton for non-convex optimization. CoRR Jim Zhao, Aurélien Lucchi, Nikita Doikov
2024	A*	`conf`	Initial Guessing Bias: How Untrained Networks Favor Some Classes. ICML Emanuele Francazi, Aurélien Lucchi, Marco Baity-Jesi
2024	A*	`conf`	Loss Landscape Characterization of Neural Networks without Over-Parametrization. NeurIPS Rustem Islamov, Niccolò Ajroldi, Antonio Orvieto, Aurélien Lucchi
2024	J	`jnl`	Loss Landscape Characterization of Neural Networks without Over-Parametrization. CoRR Rustem Islamov, Niccolò Ajroldi, Antonio Orvieto, Aurélien Lucchi
2024	A	`conf`	SDEs for Minimax Optimization. AISTATS Enea Monzio Compagnoni, Antonio Orvieto, Hans Kersting, Frank Proske, Aurélien Lucchi
2024	J	`jnl`	SDEs for Minimax Optimization. CoRR Enea Monzio Compagnoni, Antonio Orvieto, Hans Kersting, Frank Norbert Proske, Aurélien Lucchi
2024	A*	`conf`	Theoretical Characterisation of the Gauss Newton Conditioning in Neural Networks. NeurIPS Jim Zhao, Sidak Pal Singh, Aurélien Lucchi
2024	J	`jnl`	Theoretical characterisation of the Gauss-Newton conditioning in Neural Networks. CoRR Jim Zhao, Sidak Pal Singh, Aurélien Lucchi
2023	A*	`conf`	A Theoretical Analysis of the Learning Dynamics under Class Imbalance. ICML Emanuele Francazi, Marco Baity-Jesi, Aurélien Lucchi
2023	A*	`conf`	A Theoretical Analysis of the Test Error of Finite-Rank Kernel Ridge Regression. NeurIPS Tin Sum Cheng, Aurélien Lucchi, Anastasis Kratsios, Ivan Dokmanic, David Belius
2023	J	`jnl`	A Theoretical Analysis of the Test Error of Finite-Rank Kernel Ridge Regression. CoRR Tin Sum Cheng, Aurélien Lucchi, Ivan Dokmanic, Anastasis Kratsios, David Belius
2023	A*	`conf`	An SDE for Modeling SAM: Theory and Insights. ICML Enea Monzio Compagnoni, Luca Biggio, Antonio Orvieto, Frank Norbert Proske, Hans Kersting, Aurélien Lucchi
2023	J	`jnl`	An SDE for Modeling SAM: Theory and Insights. CoRR Enea Monzio Compagnoni, Luca Biggio, Antonio Orvieto, Frank Norbert Proske, Hans Kersting, Aurélien Lucchi
2023	A*	`conf`	Dynamic Context Pruning for Efficient and Interpretable Autoregressive Transformers. NeurIPS Sotiris Anagnostidis, Dario Pavllo, Luca Biggio, Lorenzo Noci, Aurélien Lucchi, Thomas Hofmann
2023	J	`jnl`	Dynamic Context Pruning for Efficient and Interpretable Autoregressive Transformers. CoRR Sotiris Anagnostidis, Dario Pavllo, Luca Biggio, Lorenzo Noci, Aurélien Lucchi, Thomas Hofmann
2023	J	`jnl`	Initial Guessing Bias: How Untrained Networks Favor Some Classes. CoRR Emanuele Francazi, Aurélien Lucchi, Marco Baity-Jesi
2023	A*	`conf`	Mastering Spatial Graph Prediction of Road Networks. ICCV Sotiris Anagnostidis, Aurélien Lucchi, Thomas Hofmann
2023	J	`jnl`	Regret-Optimal Federated Transfer Learning for Kernel Regression with Applications in American Option Pricing. CoRR Xuwei Yang, Anastasis Kratsios, Florian Krach, Matheus R. Grasselli, Aurélien Lucchi
2022	A	`conf`	A Globally Convergent Evolutionary Strategy for Stochastic Constrained Optimization with Applications to Reinforcement Learning. AISTATS Youssef Diouane, Aurélien Lucchi, Vihang Prakash Patil
2022	J	`jnl`	A Globally Convergent Evolutionary Strategy for Stochastic Constrained Optimization with Applications to Reinforcement Learning. CoRR Youssef Diouane, Aurélien Lucchi, Vihang Patil
2022	A*	`conf`	Anticorrelated Noise Injection for Improved Generalization. ICML Antonio Orvieto, Hans Kersting, Frank Proske, Francis R. Bach, Aurélien Lucchi
2022	J	`jnl`	Anticorrelated Noise Injection for Improved Generalization. CoRR Antonio Orvieto, Hans Kersting, Frank Proske, Francis R. Bach, Aurélien Lucchi
2022	J	`jnl`	Characterizing the Effect of Class Imbalance on the Learning Dynamics. CoRR Emanuele Francazi, Marco Baity-Jesi, Aurélien Lucchi
2022	A	`conf`	Faster Single-loop Algorithms for Minimax Optimization without Strong Concavity. AISTATS Junchi Yang, Antonio Orvieto, Aurélien Lucchi, Niao He
2022	J	`jnl`	Generalization Through The Lens Of Leave-One-Out Error. CoRR Gregor Bachmann, Thomas Hofmann, Aurélien Lucchi
2022	A*	`conf`	Generalization Through the Lens of Leave-One-Out Error. ICLR Gregor Bachmann, Thomas Hofmann, Aurélien Lucchi
2022	J	`jnl`	Mastering Spatial Graph Prediction of Road Networks. CoRR Sotiris Anagnostidis, Aurélien Lucchi, Thomas Hofmann
2022	A*	`conf`	On the Theoretical Properties of Noise Correlation in Stochastic Optimization. NeurIPS Aurélien Lucchi, Frank Proske, Antonio Orvieto, Francis R. Bach, Hans Kersting
2022	J	`jnl`	On the Theoretical Properties of Noise Correlation in Stochastic Optimization. CoRR Aurélien Lucchi, Frank Proske, Antonio Orvieto, Francis R. Bach, Hans Kersting
2022	A*	`conf`	Phenomenology of Double Descent in Finite-Width Neural Networks. ICLR Sidak Pal Singh, Aurélien Lucchi, Thomas Hofmann, Bernhard Schölkopf
2022	J	`jnl`	Phenomenology of Double Descent in Finite-Width Neural Networks. CoRR Sidak Pal Singh, Aurélien Lucchi, Thomas Hofmann, Bernhard Schölkopf
2022	A*	`conf`	Signal Propagation in Transformers: Theoretical Perspectives and the Role of Rank Collapse. NeurIPS Lorenzo Noci, Sotiris Anagnostidis, Luca Biggio, Antonio Orvieto, Sidak Pal Singh, Aurélien Lucchi
2022	J	`jnl`	Signal Propagation in Transformers: Theoretical Perspectives and the Role of Rank Collapse. CoRR Lorenzo Noci, Sotiris Anagnostidis, Luca Biggio, Antonio Orvieto, Sidak Pal Singh, Aurélien Lucchi
2022	A	`conf`	Vanishing Curvature in Randomly Initialized Deep ReLU Networks. AISTATS Antonio Orvieto, Jonas Kohler, Dario Pavllo, Thomas Hofmann, Aurélien Lucchi
2021	A	`conf`	Direct-Search for a Class of Stochastic Min-Max Problems. AISTATS Sotirios-Konstantinos Anagnostidis, Aurélien Lucchi, Youssef Diouane
2021	J	`jnl`	Direct-Search for a Class of Stochastic Min-Max Problems. CoRR Sotiris Anagnostidis, Aurélien Lucchi, Youssef Diouane
2021	J	`jnl`	Emulation of Cosmological Mass Maps with Conditional Generative Adversarial Networks. Frontiers Artif. Intell. Nathanaël Perraudin, Sandro Marcon, Aurélien Lucchi, Tomasz Kacprzak
2021	J	`jnl`	Faster Single-loop Algorithms for Minimax Optimization without Strong Concavity. CoRR Junchi Yang, Antonio Orvieto, Aurélien Lucchi, Niao He
2021	J	`jnl`	Generative Minimization Networks: Training GANs Without Competition. CoRR Paulina Grnarova, Yannic Kilcher, Kfir Y. Levy, Aurélien Lucchi, Thomas Hofmann
2021	A*	`conf`	Learning Generative Models of Textured 3D Meshes from Real-World Images. ICCV Dario Pavllo, Jonas Kohler, Thomas Hofmann, Aurélien Lucchi
2021	J	`jnl`	Learning Generative Models of Textured 3D Meshes from Real-World Images. CoRR Dario Pavllo, Jonas Kohler, Thomas Hofmann, Aurélien Lucchi
2021	A	`conf`	Momentum Improves Optimization on Riemannian Manifolds. AISTATS Foivos Alimisis, Antonio Orvieto, Gary Bécigneul, Aurélien Lucchi
2021	J	`jnl`	Neural Symbolic Regression that Scales. CoRR Luca Biggio, Tommaso Bendinelli, Alexander Neitz, Aurélien Lucchi, Giambattista Parascandolo
2021	A*	`conf`	Neural Symbolic Regression that scales. ICML Luca Biggio, Tommaso Bendinelli, Alexander Neitz, Aurélien Lucchi, Giambattista Parascandolo
2021	A*	`conf`	On the Second-order Convergence Properties of Random Search Methods. NeurIPS Aurélien Lucchi, Antonio Orvieto, Adamos Solomou
2021	J	`jnl`	On the Second-order Convergence Properties of Random Search Methods. CoRR Aurélien Lucchi, Antonio Orvieto, Adamos Solomou
2021	A*	`conf`	Scalable Graph Networks for Particle Simulations. AAAI Karolis Martinkus, Aurélien Lucchi, Nathanaël Perraudin
2021	J	`jnl`	The power of quantum neural networks. Nat. Comput. Sci. Amira Abbas, David Sutter, Christa Zoufal, Aurélien Lucchi, Alessio Figalli, Stefan Woerner
2021	J	`jnl`	Vanishing Curvature and the Power of Adaptive Methods in Randomly Initialized Deep Networks. CoRR Antonio Orvieto, Jonas Kohler, Dario Pavllo, Thomas Hofmann, Aurélien Lucchi
2021	J	`jnl`	Variational quantum Boltzmann machines. Quantum Mach. Intell. Christa Zoufal, Aurélien Lucchi, Stefan Woerner
2020	A	`conf`	A Continuous-time Perspective for Modeling Acceleration in Riemannian Optimization. AISTATS Foivos Alimisis, Antonio Orvieto, Gary Bécigneul, Aurélien Lucchi
2020	A*	`conf`	An Accelerated DFO Algorithm for Finite-sum Convex Functions. ICML Yuwen Chen, Antonio Orvieto, Aurélien Lucchi
2020	J	`jnl`	An Accelerated DFO Algorithm for Finite-sum Convex Functions. CoRR Yuwen Chen, Antonio Orvieto, Aurélien Lucchi
2020	A*	`conf`	Batch normalization provably avoids ranks collapse for randomly initialised deep networks. NeurIPS Hadi Daneshmand, Jonas Moritz Kohler, Francis R. Bach, Thomas Hofmann, Aurélien Lucchi
2020	—	`conf`	Controlling Style and Semantics in Weakly-Supervised Image Generation. ECCV (6) Dario Pavllo, Aurélien Lucchi, Thomas Hofmann
2020	A*	`conf`	Convolutional Generation of Textured 3D Meshes. NeurIPS Dario Pavllo, Graham Spinks, Thomas Hofmann, Marie-Francine Moens, Aurélien Lucchi
2020	J	`jnl`	Convolutional Generation of Textured 3D Meshes. CoRR Dario Pavllo, Graham Spinks, Thomas Hofmann, Marie-Francine Moens, Aurélien Lucchi
2020	J	`jnl`	Emulation of cosmological mass maps with conditional generative adversarial networks. CoRR Nathanaël Perraudin, Sandro Marcon, Aurélien Lucchi, Tomasz Kacprzak
2020	A*	`conf`	Randomized Block-Diagonal Preconditioning for Parallel Learning. ICML Celestine Mendler-Dünner, Aurélien Lucchi
2020	J	`jnl`	Randomized Block-Diagonal Preconditioning for Parallel Learning. CoRR Celestine Mendler-Dünner, Aurélien Lucchi
2020	J	`jnl`	Scalable Graph Networks for Particle Simulations. CoRR Karolis Martinkus, Aurélien Lucchi, Nathanaël Perraudin
2020	J	`jnl`	The power of quantum neural networks. CoRR Amira Abbas, David Sutter, Christa Zoufal, Aurélien Lucchi, Alessio Figalli, Stefan Woerner
2020	J	`jnl`	Theoretical Understanding of Batch-normalization: A Markov Chain Perspective. CoRR Hadi Daneshmand, Jonas Moritz Kohler, Francis R. Bach, Thomas Hofmann, Aurélien Lucchi
2019	A*	`conf`	A Domain Agnostic Measure for Monitoring and Evaluating GANs. NeurIPS Paulina Grnarova, Kfir Y. Levy, Aurélien Lucchi, Nathanaël Perraudin, Ian J. Goodfellow, Thomas Hofmann, Andreas Krause
2019	J	`jnl`	A Stochastic Tensor Method for Non-convex Optimization. CoRR Aurélien Lucchi, Jonas Kohler
2019	A*	`conf`	Continuous-time Models for Stochastic Optimization Algorithms. NeurIPS Antonio Orvieto, Aurélien Lucchi
2019	J	`jnl`	Controlling Style and Semantics in Weakly-Supervised Image Generation. CoRR Dario Pavllo, Aurélien Lucchi, Thomas Hofmann
2019	J	`jnl`	Cosmological N-body simulations: a challenge for scalable generative models. CoRR Nathanaël Perraudin, Ankit Srivastava, Aurélien Lucchi, Tomasz Kacprzak, Thomas Hofmann, Alexandre Réfrégier
2019	J	`jnl`	Ellipsoidal Trust Region Methods and the Marginal Value of Hessian Information for Neural Network Training. CoRR Leonard Adolphs, Jonas Kohler, Aurélien Lucchi
2019	A	`conf`	Exponential convergence rates for Batch Normalization: The power of length-direction decoupling in non-convex optimization. AISTATS Jonas Moritz Kohler, Hadi Daneshmand, Aurélien Lucchi, Thomas Hofmann, Ming Zhou, Klaus Neymeyr
2019	A	`conf`	Local Saddle Point Optimization: A Curvature Exploitation Approach. AISTATS Leonard Adolphs, Hadi Daneshmand, Aurélien Lucchi, Thomas Hofmann
2019	A*	`conf`	Shadowing Properties of Optimization Algorithms. NeurIPS Antonio Orvieto, Aurélien Lucchi
2019	J	`jnl`	Shadowing Properties of Optimization Algorithms. CoRR Antonio Orvieto, Aurélien Lucchi
2019	A	`conf`	The Role of Memory in Stochastic Optimization. UAI Antonio Orvieto, Jonas Kohler, Aurélien Lucchi
2019	J	`jnl`	The Role of Memory in Stochastic Optimization. CoRR Antonio Orvieto, Jonas Kohler, Aurélien Lucchi
2019	A*	`conf`	Topological Map Extraction From Overhead Images. ICCV Zuoyue Li, Jan Dirk Wegner, Aurélien Lucchi
2018	A*	`conf`	A Distributed Second-Order Algorithm You Can Trust. ICML Celestine Dünner, Aurélien Lucchi, Matilde Gargiani, An Bian, Thomas Hofmann, Martin Jaggi
2018	J	`jnl`	A Distributed Second-Order Algorithm You Can Trust. CoRR Celestine Dünner, Aurélien Lucchi, Matilde Gargiani, An Bian, Thomas Hofmann, Martin Jaggi
2018	J	`jnl`	Adversarially Robust Training through Structured Gradient Regularization. CoRR Kevin Roth, Aurélien Lucchi, Sebastian Nowozin, Thomas Hofmann
2018	—	`conf`	An Online Learning Approach to Generative Adversarial Networks. ICLR (Poster) Paulina Grnarova, Kfir Y. Levy, Aurélien Lucchi, Thomas Hofmann, Andreas Krause
2018	J	`jnl`	Continuous-time Models for Stochastic Optimization Algorithms. CoRR Antonio Orvieto, Aurélien Lucchi
2018	A*	`conf`	Escaping Saddles with Stochastic Gradients. ICML Hadi Daneshmand, Jonas Moritz Kohler, Aurélien Lucchi, Thomas Hofmann
2018	J	`jnl`	Escaping Saddles with Stochastic Gradients. CoRR Hadi Daneshmand, Jonas Moritz Kohler, Aurélien Lucchi, Thomas Hofmann
2018	J	`jnl`	Evaluating GANs via Duality. CoRR Paulina Grnarova, Kfir Y. Levy, Aurélien Lucchi, Nathanaël Perraudin, Thomas Hofmann, Andreas Krause
2018	J	`jnl`	Local Saddle Point Optimization: A Curvature Exploitation Approach. CoRR Leonard Adolphs, Hadi Daneshmand, Aurélien Lucchi, Thomas Hofmann
2018	J	`jnl`	PolyMapper: Extracting City Maps using Polygons. CoRR Zuoyue Li, Jan Dirk Wegner, Aurélien Lucchi
2018	—	`conf`	Semantic Interpolation in Implicit Models. ICLR (Poster) Yannic Kilcher, Aurélien Lucchi, Thomas Hofmann
2018	J	`jnl`	Towards a Theoretical Understanding of Batch Normalization. CoRR Jonas Moritz Kohler, Hadi Daneshmand, Aurélien Lucchi, Ming Zhou, Klaus Neymeyr, Thomas Hofmann
2017	J	`jnl`	An Online Learning Approach to Generative Adversarial Networks. CoRR Paulina Grnarova, Kfir Y. Levy, Aurélien Lucchi, Thomas Hofmann, Andreas Krause
2017	J	`jnl`	Flexible Prior Distributions for Deep Generative Models. CoRR Yannic Kilcher, Aurélien Lucchi, Thomas Hofmann
2017	J	`jnl`	Generator Reversal. CoRR Yannic Kilcher, Aurélien Lucchi, Thomas Hofmann
2017	J	`jnl`	Learning Aerial Image Segmentation From Online Maps. IEEE Trans. Geosci. Remote. Sens. Pascal Kaiser, Jan Dirk Wegner, Aurélien Lucchi, Martin Jaggi, Thomas Hofmann, Konrad Schindler
2017	J	`jnl`	Learning Aerial Image Segmentation from Online Maps. CoRR Pascal Kaiser, Jan Dirk Wegner, Aurélien Lucchi, Martin Jaggi, Thomas Hofmann, Konrad Schindler
2017	A*	`conf`	Leveraging Large Amounts of Weakly Supervised Data for Multi-Language Sentiment Classification. WWW Jan Deriu, Aurélien Lucchi, Valeria De Luca, Aliaksei Severyn, Simon Müller, Mark Cieliebak, Thomas Hofmann, Martin Jaggi
2017	J	`jnl`	Leveraging Large Amounts of Weakly Supervised Data for Multi-Language Sentiment Classification. CoRR Jan Deriu, Aurélien Lucchi, Valeria De Luca, Aliaksei Severyn, Simon Müller, Mark Cieliebak, Thomas Hofmann, Martin Jaggi
2017	J	`jnl`	Radio frequency interference mitigation using deep convolutional neural networks. Astron. Comput. Joël Akeret, Chihway L. Chang, Aurélien Lucchi, Alexandre Réfrégier
2017	J	`jnl`	Semantic Interpolation in Implicit Models. CoRR Yannic Kilcher, Aurélien Lucchi, Thomas Hofmann
2017	—	`conf`	Stabilizing Training of Generative Adversarial Networks through Regularization. NIPS Kevin Roth, Aurélien Lucchi, Sebastian Nowozin, Thomas Hofmann
2017	J	`jnl`	Stabilizing Training of Generative Adversarial Networks through Regularization. CoRR Kevin Roth, Aurélien Lucchi, Sebastian Nowozin, Thomas Hofmann
2017	A*	`conf`	Sub-sampled Cubic Regularization for Non-convex Optimization. ICML Jonas Moritz Kohler, Aurélien Lucchi
2017	J	`jnl`	Sub-sampled Cubic Regularization for Non-convex Optimization. CoRR Jonas Moritz Kohler, Aurélien Lucchi
2016	—	`conf`	Adaptive Newton Method for Empirical Risk Minimization to Statistical Accuracy. NIPS Aryan Mokhtari, Hadi Daneshmand, Aurélien Lucchi, Thomas Hofmann, Alejandro Ribeiro
2016	J	`jnl`	Bootstrap, Review, Decode: Using Out-of-Domain Textual Data to Improve Image Captioning. CoRR Wenhu Chen, Aurélien Lucchi, Thomas Hofmann
2016	J	`jnl`	DynaNewton - Accelerating Newton's Method for Machine Learning. CoRR Hadi Daneshmand, Aurélien Lucchi, Thomas Hofmann
2016	A*	`conf`	Probabilistic Bag-Of-Hyperlinks Model for Entity Linking. WWW Octavian-Eugen Ganea, Marina Ganea, Aurélien Lucchi, Carsten Eickhoff, Thomas Hofmann
2016	A*	`conf`	Starting Small - Learning with Adaptive Sample Sizes. ICML Hadi Daneshmand, Aurélien Lucchi, Thomas Hofmann
2016	J	`jnl`	Starting Small - Learning with Adaptive Sample Sizes. CoRR Hadi Daneshmand, Aurélien Lucchi, Thomas Hofmann
2016	—	`conf`	SwissCheese at SemEval-2016 Task 4: Sentiment Classification Using an Ensemble of Convolutional Neural Networks with Distant Supervision. SemEval@NAACL-HLT Jan Deriu, Maurice Gonzenbach, Fatih Uzdilli, Aurélien Lucchi, Valeria De Luca, Martin Jaggi
2015	J	`jnl`	A Variance Reduced Stochastic Newton Method. CoRR Aurélien Lucchi, Brian McWilliams, Thomas Hofmann
2015	J	`jnl`	Learning Structured Models for Segmentation of 2-D and 3-D Imagery. IEEE Trans. Medical Imaging Aurélien Lucchi, Pablo Márquez-Neila, Carlos J. Becker, Yunpeng Li, Kevin Smith, Graham Knott, Pascal Fua
2015	J	`jnl`	Neighborhood Watch: Stochastic Gradient Descent with Neighbors. CoRR Thomas Hofmann, Aurélien Lucchi, Brian McWilliams
2015	J	`jnl`	Probabilistic Bag-Of-Hyperlinks Model for Entity Linking. CoRR Octavian-Eugen Ganea, Marina Horlescu, Aurélien Lucchi, Carsten Eickhoff, Thomas Hofmann
2015	—	`conf`	Variance Reduced Stochastic Gradient Descent with Neighbors. NIPS Thomas Hofmann, Aurélien Lucchi, Simon Lacoste-Julien, Brian McWilliams
2014	—	`conf`	Exploiting Enclosing Membranes and Contextual Cues for Mitochondria Segmentation. MICCAI (1) Aurélien Lucchi, Carlos J. Becker, Pablo Márquez-Neila, Pascal Fua
2013	—	`conf`	An Optimal Policy for Target Localization with Application to Electron Microscopy. ICML (1) Raphael Sznitman, Aurélien Lucchi, Peter I. Frazier, Bruno Jedynak, Pascal Fua
2013	—	`conf`	Flash Scanning Electron Microscopy. MICCAI (3) Raphael Sznitman, Aurélien Lucchi, Marco Cantoni, Graham Knott, Pascal Fua
2013	—	`—`	Learning Discriminative Features and Structured Models for Segmentation in Microscopy and Natural Images. Aurélien Lucchi
2013	A*	`conf`	Learning for Structured Prediction Using Approximate Subgradient Descent with Working Sets. CVPR Aurélien Lucchi, Yunpeng Li, Pascal Fua
2012	—	`conf`	Efficient Scanning for EM Based Target Localization. MICCAI (3) Raphael Sznitman, Aurélien Lucchi, Natasa Pjescic-Emedji, Graham Knott, Pascal Fua
2012	—	`conf`	Joint Image and Word Sense Discrimination for Image Retrieval. ECCV (1) Aurélien Lucchi, Jason Weston
2012	J	`jnl`	SLIC Superpixels Compared to State-of-the-Art Superpixel Methods. IEEE Trans. Pattern Anal. Mach. Intell. Radhakrishna Achanta, Appu Shaji, Kevin Smith, Aurélien Lucchi, Pascal Fua, Sabine Süsstrunk
2012	—	`conf`	Structured Image Segmentation Using Kernelized Features. ECCV (2) Aurélien Lucchi, Yunpeng Li, Kevin Smith, Pascal Fua
2012	J	`jnl`	Supervoxel-Based Segmentation of Mitochondria in EM Image Stacks With Learned Shape Features. IEEE Trans. Medical Imaging Aurélien Lucchi, Kevin Smith, Radhakrishna Achanta, Graham Knott, Pascal Fua
2011	A*	`conf`	Are spatial and global constraints really necessary for segmentation? ICCV Aurélien Lucchi, Yunpeng Li, Xavier Boix Bosch, Kevin Smith, Pascal Fua
2010	—	`conf`	A Fully Automated Approach to Segmentation of Irregularly Shaped Cellular Structures in EM Images. MICCAI (2) Aurélien Lucchi, Kevin Smith, Radhakrishna Achanta, Vincent Lepetit, Pascal Fua
2010	B	`conf`	An empirical evaluation of touch and tangible interfaces for tabletop displays. TEI Aurélien Lucchi, Patrick Jermann, Guillaume Zufferey, Pierre Dillenbourg
2009	—	`conf`	Physical space and division of labor around a tabletop tangible simulation. CSCL (1) Patrick Jermann, Guillaume Zufferey, Bertrand Schneider, Aurélien Lucchi, Simon Lépine, Pierre Dillenbourg
2009	B	`conf`	TinkerSheets: using paper forms to control and visualize tangible simulations. TEI Guillaume Zufferey, Patrick Jermann, Aurélien Lucchi, Pierre Dillenbourg