Timezone: »
Sparse representation and low-rank approximation are fundamental tools in fields as diverse as computer vision, computational biology, signal processing, natural language processing, and machine learning. Recent advances in sparse and low-rank modeling have led to increasingly concise descriptions of high dimensional data, together with algorithms of provable performance and bounded complexity. Our workshop aims to survey recent work on sparsity and low-rank approximation and to provide a forum for open discussion of the key questions concerning these dimensionality reduction techniques. The workshop will be divided into two segments, a "sparsity segment" emphasizing sparse dictionary learning and a "low-rank segment" emphasizing scalability and large data.
The sparsity segment will be dedicated to learning sparse latent representations and dictionaries: decomposing a signal or a vector of observations as sparse linear combinations of basis vectors, atoms or covariates is ubiquitous in machine learning and signal processing. Algorithms and theoretical analyses for obtaining these decompositions are now numerous. Learning the atoms or basis vectors directly from data has proven useful in several domains and is often seen from different view points: (a) as a matrix factorization problem with potentially some constraints such as pointwise nonnegativity, (b) as a latent variable model which can be treated in a probabilistic and potentially Bayesian way, leading in particular to topic models, and (c) as dictionary learning with often a goal of signal representation or restoration. The goal of this part of the workshop is to confront these various points of view and foster exchanges of ideas among the signal processing, statistics, machine learning and applied mathematics communities.
The low-rank segment will explore the impact of low-rank methods for large-scale machine learning. Large datasets often take the form of matrices representing either a set of real-valued features for each datapoint or pairwise similarities between datapoints. Hence, modern learning problems face the daunting task of storing and operating on matrices with millions to billions of entries. An attractive solution to this problem involves working with low-rank approximations of the original matrix. Low-rank approximation is at the core of widely used algorithms such as Principal Component Analysis and Latent Semantic Indexing, and low-rank matrices appear in a variety of applications including lossy data compression, collaborative filtering, image processing, text analysis, matrix completion, robust matrix factorization and metric learning. In this segment we aim to study new algorithms, recent theoretical advances and large-scale empirical results, and more broadly we hope to identify additional interesting scenarios for use of low-rank approximations for learning tasks.
Author Information
Ameet S Talwalkar (CMU)
Lester W Mackey (University of California, Berkeley)
Mehryar Mohri (Courant Inst. of Math. Sciences & Google Research)
Michael W Mahoney (UC Berkeley)
Francis Bach (INRIA - Ecole Normale Superieure)
Mike Davies (University of Edinburgh)
Remi Gribonval (INRIA)
Guillaume R Obozinski (Ecole des Ponts - ParisTech)
More from the Same Authors
-
2021 Spotlight: Agnostic Reinforcement Learning with Low-Rank MDPs and Rich Observations »
Ayush Sekhari · Christoph Dann · Mehryar Mohri · Yishay Mansour · Karthik Sridharan -
2021 Spotlight: Batch Normalization Orthogonalizes Representations in Deep Random Networks »
Hadi Daneshmand · Amir Joudaki · Francis Bach -
2021 Spotlight: On the Existence of The Adversarial Bayes Classifier »
Pranjal Awasthi · Natalie Frank · Mehryar Mohri -
2021 Spotlight: Beyond Value-Function Gaps: Improved Instance-Dependent Regret Bounds for Episodic Reinforcement Learning »
Christoph Dann · Teodor Vanislavov Marinov · Mehryar Mohri · Julian Zimmert -
2021 Spotlight: Calibration and Consistency of Adversarial Surrogate Losses »
Pranjal Awasthi · Natalie Frank · Anqi Mao · Mehryar Mohri · Yutao Zhong -
2021 : Simulated User Studies for Explanation Evaluation »
Valerie Chen · Gregory Plumb · Nicholay Topin · Ameet S Talwalkar -
2021 : Bayesian Persuasion for Algorithmic Recourse »
Keegan Harris · Valerie Chen · Joon Kim · Ameet S Talwalkar · Hoda Heidari · Steven Wu -
2021 : Bayesian Persuasion for Algorithmic Recourse »
Keegan Harris · Valerie Chen · Joon Kim · Ameet S Talwalkar · Hoda Heidari · Steven Wu -
2022 Poster: A Non-asymptotic Analysis of Non-parametric Temporal-Difference Learning »
Eloïse Berthier · Ziad Kobeissi · Francis Bach -
2022 : A Theory of Learning with Competing Objectives and User Feedback »
Pranjal Awasthi · Corinna Cortes · Yishay Mansour · Mehryar Mohri -
2022 : AdaME: Adaptive learning of multisource adaptationensembles »
Scott Yak · Javier Gonzalvo · Mehryar Mohri · Corinna Cortes -
2022 : A Theory of Learning with Competing Objectives and User Feedback »
Pranjal Awasthi · Corinna Cortes · Yishay Mansour · Mehryar Mohri -
2023 Poster: On the impact of activation and normalization in obtaining isometric embeddings at initialization »
Amir Joudaki · Hadi Daneshmand · Francis Bach -
2023 Poster: Differentiable Clustering with Perturbed Spanning Forests »
Lawrence Stewart · Francis Bach · Felipe Llinares-Lopez · Quentin Berthet -
2023 Poster: $H$-Consistency Bounds: Characterization and Extensions »
Anqi Mao · Mehryar Mohri · Yutao Zhong -
2023 Poster: Abide by the law and follow the flow: conservation laws for gradient flows »
Sibylle Marcotte · Remi Gribonval · Gabriel Peyré -
2023 Poster: Does a sparse ReLU network training problem always admit an optimum ? »
TUNG LE · Remi Gribonval · Elisa Riccietti -
2023 Poster: Structured Prediction with Stronger Consistency Guarantees »
Anqi Mao · Mehryar Mohri · Yutao Zhong -
2023 Poster: Regularization properties of adversarially-trained linear regression »
Antonio Ribeiro · Dave Zachariah · Francis Bach · Thomas Schön -
2023 Poster: Two-Stage Learning to Defer with Multiple Experts »
Anqi Mao · Mehryar Mohri · Yutao Zhong -
2023 Oral: Abide by the law and follow the flow: conservation laws for gradient flows »
Sibylle Marcotte · Remi Gribonval · Gabriel Peyré -
2022 Spotlight: Lightning Talks 6A-2 »
Yichuan Mo · Botao Yu · Gang Li · Zezhong Xu · Haoran Wei · Arsene Fansi Tchango · Raef Bassily · Haoyu Lu · Qi Zhang · Songming Liu · Mingyu Ding · Peiling Lu · Yifei Wang · Xiang Li · Dongxian Wu · Ping Guo · Wen Zhang · Hao Zhongkai · Mehryar Mohri · Rishab Goel · Yisen Wang · Yifei Wang · Yangguang Zhu · Zhi Wen · Ananda Theertha Suresh · Chengyang Ying · Yujie Wang · Peng Ye · Rui Wang · Nanyi Fei · Hui Chen · Yiwen Guo · Wei Hu · Chenglong Liu · Julien Martel · Yuqi Huo · Wu Yichao · Hang Su · Yisen Wang · Peng Wang · Huajun Chen · Xu Tan · Jun Zhu · Ding Liang · Zhiwu Lu · Joumana Ghosn · Shanshan Zhang · Wei Ye · Ze Cheng · Shikun Zhang · Tao Qin · Tie-Yan Liu -
2022 Spotlight: Differentially Private Learning with Margin Guarantees »
Raef Bassily · Mehryar Mohri · Ananda Theertha Suresh -
2022 Spotlight: Lightning Talks 1A-4 »
Siwei Wang · Jing Liu · Nianqiao Ju · Shiqian Li · Eloïse Berthier · Muhammad Faaiz Taufiq · Arsene Fansi Tchango · Chen Liang · Chulin Xie · Jordan Awan · Jean-Francois Ton · Ziad Kobeissi · Wenguan Wang · Xinwang Liu · Kewen Wu · Rishab Goel · Jiaxu Miao · Suyuan Liu · Julien Martel · Ruobin Gong · Francis Bach · Chi Zhang · Rob Cornish · Sanmi Koyejo · Zhi Wen · Yee Whye Teh · Yi Yang · Jiaqi Jin · Bo Li · Yixin Zhu · Vinayak Rao · Wenxuan Tu · Gaetan Marceau Caron · Arnaud Doucet · Xinzhong Zhu · Joumana Ghosn · En Zhu -
2022 Spotlight: A Non-asymptotic Analysis of Non-parametric Temporal-Difference Learning »
Eloïse Berthier · Ziad Kobeissi · Francis Bach -
2022 : A Theory of Learning with Competing Objectives and User Feedback »
Pranjal Awasthi · Corinna Cortes · Yishay Mansour · Mehryar Mohri -
2022 : Invited Talk #1, Differentially Private Learning with Margin Guarantees, Mehryar Mohri »
Mehryar Mohri -
2022 Poster: Variational inference via Wasserstein gradient flows »
Marc Lambert · Sinho Chewi · Francis Bach · Silvère Bonnabel · Philippe Rigollet -
2022 Poster: Unsupervised Learning From Incomplete Measurements for Inverse Problems »
Julián Tachella · Dongdong Chen · Mike Davies -
2022 Poster: Multi-Class $H$-Consistency Bounds »
Pranjal Awasthi · Anqi Mao · Mehryar Mohri · Yutao Zhong -
2022 Poster: Asynchronous SGD Beats Minibatch SGD Under Arbitrary Delays »
Konstantin Mishchenko · Francis Bach · Mathieu Even · Blake Woodworth -
2022 Poster: Stochastic Online Learning with Feedback Graphs: Finite-Time and Asymptotic Optimality »
Teodor Vanislavov Marinov · Mehryar Mohri · Julian Zimmert -
2022 Poster: On the Theoretical Properties of Noise Correlation in Stochastic Optimization »
Aurelien Lucchi · Frank Proske · Antonio Orvieto · Francis Bach · Hans Kersting -
2022 Poster: Differentially Private Learning with Margin Guarantees »
Raef Bassily · Mehryar Mohri · Ananda Theertha Suresh -
2022 Poster: Fast Stochastic Composite Minimization and an Accelerated Frank-Wolfe Algorithm under Parallelization »
Benjamin Dubois-Taine · Francis Bach · Quentin Berthet · Adrien Taylor -
2022 Poster: Active Labeling: Streaming Stochastic Gradients »
Vivien Cabannes · Francis Bach · Vianney Perchet · Alessandro Rudi -
2021 : [S9] Simulated User Studies for Explanation Evaluation »
Valerie Chen · Gregory Plumb · Nicholay Topin · Ameet S Talwalkar -
2021 Test Of Time: Online Learning for Latent Dirichlet Allocation »
Matthew Hoffman · Francis Bach · David Blei -
2021 Poster: A Provably Efficient Model-Free Posterior Sampling Method for Episodic Reinforcement Learning »
Christoph Dann · Mehryar Mohri · Tong Zhang · Julian Zimmert -
2021 Poster: On the Existence of The Adversarial Bayes Classifier »
Pranjal Awasthi · Natalie Frank · Mehryar Mohri -
2021 Poster: Beyond Value-Function Gaps: Improved Instance-Dependent Regret Bounds for Episodic Reinforcement Learning »
Christoph Dann · Teodor Vanislavov Marinov · Mehryar Mohri · Julian Zimmert -
2021 Poster: Learning with User-Level Privacy »
Daniel Levy · Ziteng Sun · Kareem Amin · Satyen Kale · Alex Kulesza · Mehryar Mohri · Ananda Theertha Suresh -
2021 Poster: Boosting with Multiple Sources »
Corinna Cortes · Mehryar Mohri · Dmitry Storcheus · Ananda Theertha Suresh -
2021 Poster: Breaking the centralized barrier for cross-device federated learning »
Sai Praneeth Karimireddy · Martin Jaggi · Satyen Kale · Mehryar Mohri · Sashank Reddi · Sebastian Stich · Ananda Theertha Suresh -
2021 Poster: Overcoming the curse of dimensionality with Laplacian regularization in semi-supervised learning »
Vivien Cabannes · Loucas Pillaud-Vivien · Francis Bach · Alessandro Rudi -
2021 Poster: Agnostic Reinforcement Learning with Low-Rank MDPs and Rich Observations »
Ayush Sekhari · Christoph Dann · Mehryar Mohri · Yishay Mansour · Karthik Sridharan -
2021 Oral: Continuized Accelerations of Deterministic and Stochastic Gradient Descents, and of Gossip Algorithms »
Mathieu Even · Raphaël Berthier · Francis Bach · Nicolas Flammarion · Hadrien Hendrikx · Pierre Gaillard · Laurent Massoulié · Adrien Taylor -
2021 Poster: Batch Normalization Orthogonalizes Representations in Deep Random Networks »
Hadi Daneshmand · Amir Joudaki · Francis Bach -
2021 Poster: Continuized Accelerations of Deterministic and Stochastic Gradient Descents, and of Gossip Algorithms »
Mathieu Even · Raphaël Berthier · Francis Bach · Nicolas Flammarion · Hadrien Hendrikx · Pierre Gaillard · Laurent Massoulié · Adrien Taylor -
2021 Poster: Calibration and Consistency of Adversarial Surrogate Losses »
Pranjal Awasthi · Natalie Frank · Anqi Mao · Mehryar Mohri · Yutao Zhong -
2020 : Francis Bach - Where is Machine Learning Going? »
Francis Bach -
2020 Poster: Tight Nonparametric Convergence Rates for Stochastic Gradient Descent under the Noiseless Linear Model »
Raphaël Berthier · Francis Bach · Pierre Gaillard -
2020 Poster: Learning with Differentiable Pertubed Optimizers »
Quentin Berthet · Mathieu Blondel · Olivier Teboul · Marco Cuturi · Jean-Philippe Vert · Francis Bach -
2020 Poster: Batch normalization provably avoids ranks collapse for randomly initialised deep networks »
Hadi Daneshmand · Jonas Kohler · Francis Bach · Thomas Hofmann · Aurelien Lucchi -
2020 Poster: Non-parametric Models for Non-negative Functions »
Ulysse Marteau-Ferey · Francis Bach · Alessandro Rudi -
2020 Poster: Adapting to Misspecification in Contextual Bandits »
Dylan Foster · Claudio Gentile · Mehryar Mohri · Julian Zimmert -
2020 Spotlight: Non-parametric Models for Non-negative Functions »
Ulysse Marteau-Ferey · Francis Bach · Alessandro Rudi -
2020 Session: Orals & Spotlights Track 30: Optimization/Theory »
Yuxin Chen · Francis Bach -
2020 Poster: Dual-Free Stochastic Decentralized Optimization with Variance Reduction »
Hadrien Hendrikx · Francis Bach · Laurent Massoulié -
2020 Poster: Agnostic Learning with Multiple Objectives »
Corinna Cortes · Mehryar Mohri · Javier Gonzalvo · Dmitry Storcheus -
2020 Poster: Reinforcement Learning with Feedback Graphs »
Christoph Dann · Yishay Mansour · Mehryar Mohri · Ayush Sekhari · Karthik Sridharan -
2020 Poster: PAC-Bayes Learning Bounds for Sample-Dependent Priors »
Pranjal Awasthi · Satyen Kale · Stefani Karp · Mehryar Mohri -
2019 : Mehryar Mohri, "Learning with Sample-Dependent Hypothesis Sets" »
Mehryar Mohri -
2019 Poster: Learning GANs and Ensembles Using Discrepancy »
Ben Adlam · Corinna Cortes · Mehryar Mohri · Ningshan Zhang -
2019 Poster: Bandits with Feedback Graphs and Switching Costs »
Raman Arora · Teodor Vanislavov Marinov · Mehryar Mohri -
2019 Poster: Don't take it lightly: Phasing optical random projections with unknown operators »
Sidharth Gupta · Remi Gribonval · Laurent Daudet · Ivan Dokmanić -
2019 Poster: Regularized Gradient Boosting »
Corinna Cortes · Mehryar Mohri · Dmitry Storcheus -
2019 Poster: Fast Decomposable Submodular Function Minimization using Constrained Total Variation »
Senanayak Sesh Kumar Karri · Francis Bach · Thomas Pock -
2019 Poster: Towards closing the gap between the theory and practice of SVRG »
Othmane Sebbouh · Nidham Gazagnadou · Samy Jelassi · Francis Bach · Robert Gower -
2019 Poster: An Accelerated Decentralized Stochastic Proximal Algorithm for Finite Sums »
Hadrien Hendrikx · Francis Bach · Laurent Massoulié -
2019 Poster: On Lazy Training in Differentiable Programming »
Lénaïc Chizat · Edouard Oyallon · Francis Bach -
2019 Poster: Implicit Regularization of Discrete Gradient Dynamics in Linear Neural Networks »
Gauthier Gidel · Francis Bach · Simon Lacoste-Julien -
2019 Poster: Massively scalable Sinkhorn distances via the Nyström method »
Jason Altschuler · Francis Bach · Alessandro Rudi · Jonathan Niles-Weed -
2019 Poster: Hypothesis Set Stability and Generalization »
Dylan Foster · Spencer Greenberg · Satyen Kale · Haipeng Luo · Mehryar Mohri · Karthik Sridharan -
2019 Poster: Localized Structured Prediction »
Carlo Ciliberto · Francis Bach · Alessandro Rudi -
2019 Poster: UniXGrad: A Universal, Adaptive Algorithm with Optimal Guarantees for Constrained Optimization »
Ali Kavis · Kfir Y. Levy · Francis Bach · Volkan Cevher -
2019 Spotlight: UniXGrad: A Universal, Adaptive Algorithm with Optimal Guarantees for Constrained Optimization »
Ali Kavis · Kfir Y. Levy · Francis Bach · Volkan Cevher -
2019 Poster: Partially Encrypted Deep Learning using Functional Encryption »
Théo Ryffel · David Pointcheval · Francis Bach · Edouard Dufour-Sans · Romain Gay -
2019 Poster: Globally Convergent Newton Methods for Ill-conditioned Generalized Self-concordant Losses »
Ulysse Marteau-Ferey · Francis Bach · Alessandro Rudi -
2018 Poster: Optimal Algorithms for Non-Smooth Distributed Optimization in Networks »
Kevin Scaman · Francis Bach · Sebastien Bubeck · Laurent Massoulié · Yin Tat Lee -
2018 Poster: Policy Regret in Repeated Games »
Raman Arora · Michael Dinitz · Teodor Vanislavov Marinov · Mehryar Mohri -
2018 Poster: Statistical Optimality of Stochastic Gradient Descent on Hard Learning Problems through Multiple Passes »
Loucas Pillaud-Vivien · Alessandro Rudi · Francis Bach -
2018 Oral: Optimal Algorithms for Non-Smooth Distributed Optimization in Networks »
Kevin Scaman · Francis Bach · Sebastien Bubeck · Laurent Massoulié · Yin Tat Lee -
2018 Poster: Relating Leverage Scores and Density using Regularized Christoffel Functions »
Edouard Pauwels · Francis Bach · Jean-Philippe Vert -
2018 Poster: Efficient Gradient Computation for Structured Output Learning with Rational and Tropical Losses »
Corinna Cortes · Vitaly Kuznetsov · Mehryar Mohri · Dmitry Storcheus · Scott Yang -
2018 Poster: Efficient Algorithms for Non-convex Isotonic Regression through Submodular Optimization »
Francis Bach -
2018 Poster: Rest-Katyusha: Exploiting the Solution's Structure via Scheduled Restart Schemes »
Junqi Tang · Mohammad Golbabaee · Francis Bach · Mike Davies -
2018 Poster: MULAN: A Blind and Off-Grid Method for Multichannel Echo Retrieval »
Helena Peic Tukuljac · Antoine Deleforge · Remi Gribonval -
2018 Poster: Algorithms and Theory for Multiple-Source Adaptation »
Judy Hoffman · Mehryar Mohri · Ningshan Zhang -
2018 Poster: SING: Symbol-to-Instrument Neural Generator »
Alexandre Defossez · Neil Zeghidour · Nicolas Usunier · Leon Bottou · Francis Bach -
2018 Poster: On the Global Convergence of Gradient Descent for Over-parameterized Models using Optimal Transport »
Lénaïc Chizat · Francis Bach -
2017 : Concluding remarks »
Francis Bach · Benjamin Guedj · Pascal Germain -
2017 : Neil Lawrence, Francis Bach and François Laviolette »
Neil Lawrence · Francis Bach · Francois Laviolette -
2017 : Sharp asymptotic and finite-sample rates of convergence of empirical measures in Wasserstein distance »
Francis Bach -
2017 : Overture »
Benjamin Guedj · Francis Bach · Pascal Germain -
2017 Workshop: (Almost) 50 shades of Bayesian Learning: PAC-Bayesian trends and insights »
Benjamin Guedj · Pascal Germain · Francis Bach -
2017 : Mehryar Mohri (NYU) on Tight Learning Bounds for Multi-Class Classification »
Mehryar Mohri -
2017 : (Invited Talk) Mehryar Mohri: Regret minimization against strategic buyers. »
Mehryar Mohri -
2017 Poster: On Structured Prediction Theory with Calibrated Convex Surrogate Losses »
Anton Osokin · Francis Bach · Simon Lacoste-Julien -
2017 Poster: Discriminative State Space Models »
Vitaly Kuznetsov · Mehryar Mohri -
2017 Oral: On Structured Prediction Theory with Calibrated Convex Surrogate Losses »
Anton Osokin · Francis Bach · Simon Lacoste-Julien -
2017 Poster: Nonlinear Acceleration of Stochastic Algorithms »
Damien Scieur · Francis Bach · Alexandre d'Aspremont -
2017 Poster: Online Learning with Transductive Regret »
Scott Yang · Mehryar Mohri -
2017 Poster: Parameter-Free Online Learning via Model Selection »
Dylan J Foster · Satyen Kale · Mehryar Mohri · Karthik Sridharan -
2017 Spotlight: Parameter-Free Online Learning via Model Selection »
Dylan J Foster · Satyen Kale · Mehryar Mohri · Karthik Sridharan -
2017 Spotlight: Online Learning with Transductive Regret »
Scott Yang · Mehryar Mohri -
2017 Poster: Variable Importance Using Decision Trees »
Jalil Kazemitabar · Arash Amini · Adam Bloniarz · Ameet S Talwalkar -
2017 Poster: Union of Intersections (UoI) for Interpretable Data Driven Discovery and Prediction »
Kristofer Bouchard · Alejandro Bujan · Farbod Roosta-Khorasani · Shashanka Ubaru · Mr. Prabhat · Antoine Snijders · Jian-Hua Mao · Edward Chang · Michael W Mahoney · Sharmodeep Bhattacharya -
2017 Poster: Integration Methods and Optimization Algorithms »
Damien Scieur · Vincent Roulet · Francis Bach · Alexandre d'Aspremont -
2017 Poster: Federated Multi-Task Learning »
Virginia Smith · Chao-Kai Chiang · Maziar Sanjabi · Ameet S Talwalkar -
2016 : Francis Bach. Harder, Better, Faster, Stronger Convergence Rates for Least-Squares Regression. »
Francis Bach -
2016 : Invited Talk: Paleo: A Performance Model for Deep Neural Networks (Ameet Talwalkar, UCLA) »
Ameet S Talwalkar -
2016 Workshop: OPT 2016: Optimization for Machine Learning »
Suvrit Sra · Francis Bach · Sashank J. Reddi · Niao He -
2016 : Submodular Functions: from Discrete to Continuous Domains »
Francis Bach -
2016 Workshop: Learning in High Dimensions with Structure »
Nikhil Rao · Prateek Jain · Hsiang-Fu Yu · Ming Yuan · Francis Bach -
2016 Poster: Structured Prediction Theory Based on Factor Graph Complexity »
Corinna Cortes · Vitaly Kuznetsov · Mehryar Mohri · Scott Yang -
2016 Poster: Parameter Learning for Log-supermodular Distributions »
Tatiana Shpakova · Francis Bach -
2016 Poster: Regularized Nonlinear Acceleration »
Damien Scieur · Alexandre d'Aspremont · Francis Bach -
2016 Oral: Regularized Nonlinear Acceleration »
Damien Scieur · Alexandre d'Aspremont · Francis Bach -
2016 Poster: Stochastic Variance Reduction Methods for Saddle-Point Problems »
Balamurugan Palaniappan · Francis Bach -
2016 Poster: PAC-Bayesian Theory Meets Bayesian Inference »
Pascal Germain · Francis Bach · Alexandre Lacoste · Simon Lacoste-Julien -
2016 Poster: Boosting with Abstention »
Corinna Cortes · Giulia DeSalvo · Mehryar Mohri -
2016 Poster: Optimistic Bandit Convex Optimization »
Scott Yang · Mehryar Mohri -
2016 Poster: Yggdrasil: An Optimized System for Training Deep Decision Trees at Scale »
Firas Abuzaid · Joseph K Bradley · Feynman Liang · Andrew Feng · Lee Yang · Matei Zaharia · Ameet S Talwalkar -
2016 Poster: Stochastic Optimization for Large-scale Optimal Transport »
Aude Genevay · Marco Cuturi · Gabriel Peyré · Francis Bach -
2016 Tutorial: Large-Scale Optimization: Beyond Stochastic Gradient Descent and Convexity »
Suvrit Sra · Francis Bach -
2016 Tutorial: Theory and Algorithms for Forecasting Non-Stationary Time Series »
Vitaly Kuznetsov · Mehryar Mohri -
2015 : Structured Sparsity and convex optimization »
Francis Bach -
2015 : A Theory of Multiple Source Adaptation »
Mehryar Mohri -
2015 : Sharp Analysis of Random Feature Expansions »
Francis Bach -
2015 : Convergence Rates of Kernel Quadrature Rules »
Francis Bach -
2015 : Learning Theory and Algorithms for Time Series »
Mehryar Mohri -
2015 Poster: Revenue Optimization against Strategic Buyers »
Mehryar Mohri · Andres Munoz -
2015 Poster: Learning Theory and Algorithms for Forecasting Non-stationary Time Series »
Vitaly Kuznetsov · Mehryar Mohri -
2015 Oral: Learning Theory and Algorithms for Forecasting Non-stationary Time Series »
Vitaly Kuznetsov · Mehryar Mohri -
2015 Poster: Rethinking LDA: Moment Matching for Discrete ICA »
Anastasia Podosinnikova · Francis Bach · Simon Lacoste-Julien -
2015 Poster: Spectral Norm Regularization of Orthonormal Representations for Graph Transduction »
Rakesh Shivanna · Bibaswan K Chatterjee · Raman Sankaran · Chiranjib Bhattacharyya · Francis Bach -
2014 Workshop: Second Workshop on Transfer and Multi-Task Learning: Theory meets Practice »
Urun Dogan · Tatiana Tommasi · Yoshua Bengio · Francesco Orabona · Marius Kloft · Andres Munoz · Gunnar Rätsch · Hal Daumé III · Mehryar Mohri · Xuezhi Wang · Daniel Hernández-lobato · Song Liu · Thomas Unterthiner · Pascal Germain · Vinay P Namboodiri · Michael Goetz · Christopher Berlind · Sigurd Spieckermann · Marta Soare · Yujia Li · Vitaly Kuznetsov · Wenzhao Lian · Daniele Calandriello · Emilie Morvant -
2014 Workshop: Distributed Machine Learning and Matrix Computations »
Reza Zadeh · Ion Stoica · Ameet S Talwalkar -
2014 Workshop: NIPS Workshop on Transactional Machine Learning and E-Commerce »
David Parkes · David H Wolpert · Jennifer Wortman Vaughan · Jacob D Abernethy · Amos Storkey · Mark Reid · Ping Jin · Nihar Bhadresh Shah · Mehryar Mohri · Luis E Ortiz · Robin Hanson · Aaron Roth · Satyen Kale · Sebastien Lahaie -
2014 Poster: Optimal Regret Minimization in Posted-Price Auctions with Strategic Buyers »
Mehryar Mohri · Andres Munoz -
2014 Poster: Multi-Class Deep Boosting »
Vitaly Kuznetsov · Mehryar Mohri · Umar Syed -
2014 Spotlight: Optimal Regret Minimization in Posted-Price Auctions with Strategic Buyers »
Mehryar Mohri · Andres Munoz -
2014 Session: Oral Session 6 »
Mehryar Mohri -
2014 Poster: Conditional Swap Regret and Conditional Correlated Equilibrium »
Mehryar Mohri · Scott Yang -
2014 Poster: Metric Learning for Temporal Sequence Alignment »
Rémi Lajugie · Damien Garreau · Francis Bach · Sylvain Arlot -
2014 Poster: Tight convex relaxations for sparse matrix factorization »
Emile Richard · Guillaume R Obozinski · Jean-Philippe Vert -
2014 Poster: SAGA: A Fast Incremental Gradient Method With Support for Non-Strongly Convex Composite Objectives »
Aaron Defazio · Francis Bach · Simon Lacoste-Julien -
2013 Poster: Non-strongly-convex smooth stochastic approximation with convergence rate O(1/n) »
Francis Bach · Eric Moulines -
2013 Poster: Learning Kernels Using Local Rademacher Complexity »
Corinna Cortes · Marius Kloft · Mehryar Mohri -
2013 Spotlight: Non-strongly-convex smooth stochastic approximation with convergence rate O(1/n) »
Francis Bach · Eric Moulines -
2013 Spotlight: Learning Kernels Using Local Rademacher Complexity »
Corinna Cortes · Marius Kloft · Mehryar Mohri -
2013 Poster: Reconciling "priors'' & "priors" without prejudice? »
Remi Gribonval · Pierre Machart -
2013 Spotlight: Reconciling "priors'' & "priors" without prejudice? »
Remi Gribonval · Pierre Machart -
2013 Session: Oral Session 2 »
Francis Bach -
2013 Poster: Convex Relaxations for Permutation Problems »
Fajwel Fogel · Rodolphe Jenatton · Francis Bach · Alexandre d'Aspremont -
2013 Poster: Reflection methods for user-friendly submodular optimization »
Stefanie Jegelka · Francis Bach · Suvrit Sra -
2013 Session: Tutorial Session B »
Francis Bach -
2012 Workshop: Analysis Operator Learning vs. Dictionary Learning: Fraternal Twins in Sparse Modeling »
Martin Kleinsteuber · Francis Bach · Remi Gribonval · John Wright · Simon Hawe -
2012 Poster: Accuracy at the Top »
Stephen Boyd · Corinna Cortes · Mehryar Mohri · Ana Radovanovic -
2012 Poster: Multiple Operator-valued Kernel Learning »
Hachem Kadri · Alain Rakotomamonjy · Francis Bach · philippe preux -
2012 Poster: A latent factor model for highly multi-relational data »
Rodolphe Jenatton · Nicolas Le Roux · Antoine Bordes · Guillaume R Obozinski -
2012 Poster: A Stochastic Gradient Method with an Exponential Convergence
Rate for Finite Training Sets »
Nicolas Le Roux · Mark Schmidt · Francis Bach -
2012 Poster: Spectral Learning of General Weighted Automata via Constrained Matrix Completion »
Borja Balle · Mehryar Mohri -
2012 Poster: Semi-supervised Eigenvectors for Locally-biased Learning »
Toke Jansen Hansen · Michael W Mahoney -
2012 Oral: A Stochastic Gradient Method with an Exponential Convergence
Rate for Finite Training Sets »
Nicolas Le Roux · Mark Schmidt · Francis Bach -
2012 Oral: Spectral Learning of General Weighted Automata via Constrained Matrix Completion »
Borja Balle · Mehryar Mohri -
2011 Poster: Convergence Rates of Inexact Proximal-Gradient Methods for Convex Optimization »
Mark Schmidt · Nicolas Le Roux · Francis Bach -
2011 Poster: Divide-and-Conquer Matrix Factorization »
Lester W Mackey · Ameet S Talwalkar · Michael Jordan -
2011 Oral: Convergence Rates of Inexact Proximal-Gradient Methods for Convex Optimization »
Mark Schmidt · Nicolas Le Roux · Francis Bach -
2011 Poster: Non-Asymptotic Analysis of Stochastic Approximation Algorithms for Machine Learning »
Francis Bach · Eric Moulines -
2011 Poster: Trace Lasso: a trace norm regularization for correlated designs »
Edouard Grave · Guillaume R Obozinski · Francis Bach -
2011 Spotlight: Non-Asymptotic Analysis of Stochastic Approximation Algorithms for Machine Learning »
Francis Bach · Eric Moulines -
2011 Poster: Regularized Laplacian Estimation and Fast Eigenvector Approximation »
Patrick O Perry · Michael W Mahoney -
2011 Poster: Shaping Level Sets with Submodular Functions »
Francis Bach -
2010 Workshop: Low-rank Methods for Large-scale Machine Learning »
Arthur Gretton · Michael W Mahoney · Mehryar Mohri · Ameet S Talwalkar -
2010 Workshop: New Directions in Multiple Kernel Learning »
Marius Kloft · Ulrich Rueckert · Cheng Soon Ong · Alain Rakotomamonjy · Soeren Sonnenburg · Francis Bach -
2010 Spotlight: Online Learning for Latent Dirichlet Allocation »
Matthew D. Hoffman · David Blei · Francis Bach -
2010 Poster: Efficient Optimization for Discriminative Latent Class Models »
Armand Joulin · Francis Bach · Jean A Ponce -
2010 Poster: Online Learning for Latent Dirichlet Allocation »
Matthew D. Hoffman · David Blei · Francis Bach -
2010 Oral: Structured sparsity-inducing norms through submodular functions »
Francis Bach -
2010 Poster: Learning Bounds for Importance Weighting »
Corinna Cortes · Yishay Mansour · Mehryar Mohri -
2010 Poster: Structured sparsity-inducing norms through submodular functions »
Francis Bach -
2010 Poster: Network Flow Algorithms for Structured Sparsity »
Julien Mairal · Rodolphe Jenatton · Guillaume R Obozinski · Francis Bach -
2010 Poster: CUR from a Sparse Optimization Viewpoint »
Jacob Bien · Ya Xu · Michael W Mahoney -
2009 Workshop: Understanding Multiple Kernel Learning Methods »
Brian McFee · Gert Lanckriet · Francis Bach · Nati Srebro -
2009 Poster: Efficient Large-Scale Distributed Training of Conditional Maximum Entropy Models »
Gideon S Mann · Ryan McDonald · Mehryar Mohri · Nathan Silberman · Dan Walker -
2009 Poster: Ensemble Nystrom Method »
Sanjiv Kumar · Mehryar Mohri · Ameet S Talwalkar -
2009 Spotlight: Efficient Large-Scale Distributed Training of Conditional Maximum Entropy Models »
Gideon S Mann · Ryan McDonald · Mehryar Mohri · Nathan Silberman · Dan Walker -
2009 Poster: Data-driven calibration of linear estimators with minimal penalties »
Sylvain Arlot · Francis Bach -
2009 Poster: Learning Non-Linear Combinations of Kernels »
Corinna Cortes · Mehryar Mohri · Afshin Rostamizadeh -
2009 Poster: Unsupervised Feature Selection for the $k$-means Clustering Problem »
Christos Boutsidis · Michael W Mahoney · Petros Drineas -
2009 Poster: Asymptotically Optimal Regularization in Smooth Parametric Models »
Percy Liang · Francis Bach · Guillaume Bouchard · Michael Jordan -
2009 Poster: Polynomial Semantic Indexing »
Bing Bai · Jason E Weston · David Grangier · Ronan Collobert · Kunihiko Sadamasa · Yanjun Qi · Corinna Cortes · Mehryar Mohri -
2009 Tutorial: Sparse Methods for Machine Learning: Theory and Algorithms »
Francis Bach -
2008 Workshop: Kernel Learning: Automatic Selection of Optimal Kernels »
Corinna Cortes · Arthur Gretton · Gert Lanckriet · Mehryar Mohri · Afshin Rostamizadeh -
2008 Poster: Deflation Methods for Sparse PCA »
Lester W Mackey -
2008 Poster: Domain Adaptation with Multiple Sources »
Yishay Mansour · Mehryar Mohri · Afshin Rostamizadeh -
2008 Poster: Clustered Multi-Task Learning: A Convex Formulation »
Laurent Jacob · Francis Bach · Jean-Philippe Vert -
2008 Poster: High-dimensional union support recovery in multivariate regression »
Guillaume R Obozinski · Martin J Wainwright · Michael Jordan -
2008 Poster: Sparse probabilistic projections »
Cedric Archambeau · Francis Bach -
2008 Spotlight: Deflation Methods for Sparse PCA »
Lester W Mackey -
2008 Spotlight: Sparse probabilistic projections »
Cedric Archambeau · Francis Bach -
2008 Spotlight: High-dimensional union support recovery in multivariate regression »
Guillaume R Obozinski · Martin J Wainwright · Michael Jordan -
2008 Spotlight: Domain Adaptation with Multiple Sources »
Yishay Mansour · Mehryar Mohri · Afshin Rostamizadeh -
2008 Spotlight: Clustered Multi-Task Learning: A Convex Formulation »
Laurent Jacob · Francis Bach · Jean-Philippe Vert -
2008 Poster: Exploring Large Feature Spaces with Hierarchical Multiple Kernel Learning »
Francis Bach -
2008 Poster: Kernel Change-point Analysis »
Zaid Harchaoui · Francis Bach · Eric Moulines -
2008 Poster: SDL: Supervised Dictionary Learning »
Julien Mairal · Francis Bach · Jean A Ponce · Guillermo Sapiro · Andrew Zisserman -
2008 Poster: Rademacher Complexity Bounds for Non-I.I.D. Processes »
Mehryar Mohri · Afshin Rostamizadeh -
2007 Poster: Testing for Homogeneity with Kernel Fisher Discriminant Analysis »
Zaid Harchaoui · Francis Bach · Moulines Eric -
2007 Poster: DIFFRAC: a discriminative and flexible framework for clustering »
Francis Bach · Zaid Harchaoui -
2007 Session: Session 2: Probabilistic Optimization »
Francis Bach -
2007 Poster: Stability Bounds for Non-i.i.d. Processes »
Mehryar Mohri · Afshin Rostamizadeh -
2006 Poster: Active learning for misspecified generalized linear models »
Francis Bach -
2006 Poster: On Transductive Regression »
Corinna Cortes · Mehryar Mohri