Times are in Central European Time; All sessions are in the same room “Salle Dussane”. Breaks are in the “Rotonde” (the small room behind).
Note that France has its daylight saving time change on Sunday, March 27 (right before the conference). For instance, the time difference between Paris and New-York will be of 6 hours during the conference (and not just 5).
The link to access the conference is the following one https://www.virtualchair.net/events/alt-2022. It will ask for your registration e-mail, and send you a confirmation code that will let you in the virtual space.
Tuesday, March 29, 2022 | |
| 13:50-14:00 | Welcome notes, (Nika Haghtalab, Sanjoy Dasgupta) |
| 14:00-15:00 | Session 1, in person (Chair: Satyen Kale) |
| Scale-Free Adversarial Multi Armed Bandits Sudeep Raja Putta (Columbia University); Shipra Agrawal (Columbia University) | |
| Distributed Online Learning for Joint Regret with Communication Constraints Dirk van der Hoeven (Università degli Studi di Milano); Hedi Hadiji (University of Amsterdam); Tim van Erven (University of Amsterdam) | |
| Social Learning in Non-Stationary Environments Etienne Boursier (EPFL); Vianney Perchet (ENSAE & Criteo AI Lab); Marco Scarsini (LUISS) | |
| 15:30-16:30 | Session 2, virtual (Chair: Quentin Berthet) |
| Decentralized Cooperative Reinforcement Learning with Hierarchical Information Structure Hsu Kao (University of Michigan); Chen-Yu Wei (University of Southern California); Vijay Subramanian (University of Michigan) | |
| Algorithms for learning a mixture of linear classifiers Aidao Chen (Northwestern University); Anindya De (University of Pennsylvania); Aravindan Vijayaraghavan (Northwestern University) | |
| Learning with distributional inverters Eric R Binnendyk (New Mexico Institute of Mining and Technology); Marco L Carmosino (Boston University); Antonina Kolokolova (Memorial University Newfoundland); Ramyaa Ramyaa (New Mexico Institute of Mining and Technology); Manuel Sabin (UC Berkeley) | |
| 17:00-18:00 | Plenary talk, virtual (Chair: Nika Haghtalab) Sebastien Bubeck (MSR) Chasing sets, with an application to online shortest path |
| 18:30-21:00 | Welcome Reception (la Rotonde) |
Wednesday, March 30, 2022 | |
| 9:30-10:30 | Session 1, in person (Chair: Tim van Erven) |
| Global Riemannian Acceleration in Hyperbolic and Spherical Spaces David Martínez-Rubio (University of Oxford) | |
| Iterated Vector Fields and Conservatism, with Applications to Federated Learning Zachary Charles (Google Research); John K Rush (Google Research) | |
| Inductive Bias of Gradient Descent for Weight Normalized Smooth Homogeneous Neural Nets Depen Morwani (Indian Institute of Technology, Madras); Harish Guruprasad Ramaswamy (IIT Madras) | |
| 11:00-12:00 | Session 2, virtual (Chair: Sanjoy Dasgupta) |
| Efficient Local Planning with Linear Function Approximation Dong Yin (DeepMind); Botao Hao (Deepmind); Yasin Abbasi-Yadkori (DeepMind); Nevena Lazic (DeepMind); Csaba Szepesvari (DeepMind/University of Alberta) | |
| Faster Noisy Power Method Zhiqiang Xu (Baidu); Ping Li (Baidu Research) | |
| Refined Lower Bounds for Nearest Neighbor Condensation Rajesh Chitnis (University of Birmingham) | |
| 14:00-15:00 | Business Meeting, hybrid (Chair: Mehryar Mohri) |
| 15:30-16:30 | Session 4, virtual (Chair: Vianney Perchet) |
| Polynomial-Time Sum-of-Squares Can Robustly Estimate Mean and Covariance of Gaussians Optimally Peter Manohar (Carnegie Mellon University); Pravesh Kothari (Carnegie Mellon University); Brian H Zhang (Carnegie Mellon University) | |
| Understanding Simultaneous Train and Test Robustness Pranjal Awasthi (Google); Sivaraman Balakrishnan (Carnegie Mellon University); Aravindan Vijayaraghavan (Northwestern University) | |
| Improved rates for prediction and identification of partially observed linear dynamical systems Holden Lee (Duke) | |
| 17:00-18:00 | Session 5, virtual (Chair: Nika Haghtalab) |
| Faster Perturbed Stochastic Gradient Methods for Finding Local Minima Zixiang Chen (UCLA); Dongruo Zhou (UCLA); Quanquan Gu (University of California, Los Angeles) | |
| Distinguishing Relational Pattern Languages With a Small Number of Short Strings Robert Holte (University of Alberta); Seyyedmahmoud Mousavi (University of Regina); Sandra Zilles (University of Regina, Canada) | |
| Lower Bounds on the Total Variation Distance Between Mixtures of Two Gaussians Sami Davies (UW); Arya Mazumdar (University of California, San Diego); Cyrus Rashtchian (Google Research); Soumyabrata Pal (University of Massachusetts Amherst) | |
Thursday, March 31, 2022 | |
| 9:30-10:30 | Session 1, in person (Chair: Claire Vernade) |
| Metric Entropy Duality and the Sample Complexity of Outcome Indistinguishability Lunjia Hu (Stanford University); Charlotte Peale (Stanford University); Omer Reingold (Stanford University) | |
| TensorPlan and the Few Actions Lower Bound for Planning in MDPs under Linear Realizability of Optimal Value Functions Gellert Weisz (DeepMind, UCL); Csaba Szepesvari (DeepMind/University of Alberta); Andras Gyorgy (DeepMind) | |
| Asymptotic Degradation of Linear Regression Estimates with Strategic Data Sources Benjamin Roussillon (Université Grenoble-Alpes); Nicolas Gast (INRIA); Patrick Loiseau (Inria); Panayotis Mertikopoulos (CNRS and Criteo AI Lab) | |
| 11:00-12:00 | Session 2, in person (Chair: Lev Reyzin) |
| Efficient Methods for Online Multiclass Logistic Regression Naman Agarwal (Google); Satyen Kale (Google); Julian Zimmert (Google) | |
| Learning what to remember Robi Bhattacharjee (University of California, San Diego); Gaurav Mahajan (University of California, San Diego) | |
| Multicalibrated Partitions for Importance Weights Parikshit Gopalan (VMware Research); Omer Reingold (Stanford University); Vatsal Sharan (USC); Udi Wieder (VMware Research) | |
| 14:00-15:00 | Plenary talk, virtual (Chair: Sanjoy Das Gupta) Lenka Zdeborova (EPFL) Understanding trajectories of gradient-based algorithms in solvable non-convex models |
| 15:30-16:30 | Session 4, virtual (Chair: Sanjoy Das Gupta) |
| On the Last Iterate Convergence of Momentum Methods Xiaoyu Li (Boston University); Mingrui Liu (George Mason University); Francesco Orabona (Boston University) | |
| Limiting Behaviors of Nonconvex-Nonconcave Minimax Optimization via Continuous-Time Systems Benjamin Grimmer (Cornell University); Haihao Lu (University of Chicago); Pratik Worah (Google); Vahab Mirrokni (Google) | |
| On the Initialization for Convex-Concave Min-max Problems Mingrui Liu (George Mason University); Francesco Orabona (Boston University) | |
| 17:00-18:00 | Session 5, virtual (Chair: Vianney Perchet) |
| Efficient and Optimal Fixed-Time Regret with Two Experts Laura Greenstreet (University of British Columbia); Nick Harvey (University of British Columbia); Victor Portella (University of British Columbia) | |
| A Model Selection Approach for Corruption Robust Reinforcement Learning Chen-Yu Wei (University of Southern California); Chris Dann (Google); Julian Zimmert (Google) | |
| Almost Optimal Algorithms for Two-player Zero-Sum Linear Mixture Markov Games Zixiang Chen (UCLA); Dongruo Zhou (UCLA); Quanquan Gu (University of California, Los Angeles) | |
| 18:30-19:30 | Best Papers Awards Reception (la Rotonde) |
| 20:00-23:00 | Social Dinner (Marty) |
Friday, April 1, 2022 | |
| 09:30-10:30 | Session 1, virtual (Chair: Quentin Berthet) |
| Minimization by Incremental Stochastic Surrogate Optimization for Large Scale Nonconvex Problems Belhal Karimi (Baidu Research); Hoi-To Wai (Chinese University of Hong Kong); Eric Moulines (Ecole Polytechnique); Ping Li (Baidu Research) | |
| Faster Rates of Differentially Private Stochastic Convex Optimization Jinyan Su (University of Electronic Science and Technology of China); Lijie Hu (King Abdullah University of Science and Technology); Di Wang (KAUST) | |
| Adversarial Interpretation of Bayesian Inference Hisham Husain (Amazon); Jeremias Knoblauch (University College London) | |
| 11:00-1200 | Session 2, in person (Chair: Naman Agarwal) |
| Infinitely Divisible Noise in the Low Privacy Regime Nina Mesing Stausholm (IT University of Copenhagen); Rasmus Pagh (University of Copenhagen) | |
| Privacy Amplification via Shuffling for Linear Contextual Bandits Evrard Garcelon (Facebook); Kamalika Chaudhuri (University of California, San Diego); Vianney Perchet (ENSAE & Criteo AI Lab); Matteo Pirotta (Facebook AI Research) | |
| Beyond Bernoulli: Generating Random Outcomes that cannot be Distinguished from Nature Cynthia Dwork (Harvard); Michael P Kim (UC Berkeley); Omer Reingold (Stanford University); Guy N Rothblum (Weizmann Institute of Science); Gal Yona (Weizmann Institute of Science) | |
| 14:00-15:00 | Session 3, virtual (Chair: Nika Haghtalab) |
| Implicit Parameter-free Online Learning with Truncated Linear Models Keyi Chen (Boston University); Ashok Cutkosky (Boston University); Francesco Orabona (Boston University) | |
| Efficient and Optimal Algorithms for Contextual Dueling Bandits under Realizability Aadirupa Saha (Microsoft Research); Akshay Krishnamurthy (Microsoft) | |
| The Mirror Langevin Algorithm Converges with Vanishing Bias Ruilin Li (Georgia Institute of Technology); Molei Tao (Georgia Institute of Technology); Santosh Vempala (Georgia Tech); Andre Wibisono (Yale University) | |
| 15:30-16:30 | Session 4, in person (Chair: Gergo Neu) |
| Universal Online Learning with Unbounded Losses: Memory Is All You Need Moise Blanchard (Massachusetts Institute of Technology); Romain Cosson (MIT); Steve Hanneke (Purdue University) | |
| Leveraging Initial Hints for Free in Stochastic Linear Bandits Richard Zhang (Google Brain); Abhimanyu Das (Google); Ashok Cutkosky (Boston University); Chris Dann (Google) | |
| Universally Consistent Online Learning with Arbitrarily Dependent Responses Steve Hanneke (Purdue University) |