ALT18 Schedule

  1. SAT APR 7
  2. 08:30 - 08:50 Registration

    08:50 - 09:00 Opening Remarks

    09:00 - 11:00 Tutorial 1

    Learning to Optimize Revenue in Auctions.
    Renato Paes Leme and Andres Munoz Medina.

    11:00 - 11:30 Coffee Break

    11:30 - 12:30 Talks: Convergence & Optimization

    Convergence of Langevin MCMC in KL-Divergence.
    Xiang Cheng and Peter Bartlett.
    Coordinate Descent Faceoff: Primal or Dual?
    Dominik Csiba and Peter Richtarik.
    Efficient coordinate-wise leading eigenvector computation.
    Jialei Wang, Weiran Wang, Dan Garber and Nathan Srebro.

    12:30 - 13:30 Invited Talk by Eva Tardos.

    13:30 - 15:00 Lunch

    15:00 - 16:20 Talks: Bandit I

    Sparsity, variance and curvature in multi-armed bandits.
    Sebastien Bubeck, Michael Cohen and Yuanzhi Li.
    Pure Exploration in Infinitely-Armed Bandit Models with Fixed-Confidence.
    Maryam Aziz, Jesse Anderton, Emilie Kaufmann and Javed Aslam.
    The k-Nearest Neighbour UCB Algorithm for Multi-Armed Bandits with Covariates.
    Henry Reeve, Gavin Brown and Joe Mellor.
    Decision making with limited feedback: Error bounds for predictive policing and recidivism prediction.
    Danielle Ensign, Sorelle Friedler, Scott Neville, Carlos Scheidegger and Suresh Venkatasubramanian.

    16:20 - 16:50 Coffee Break

    16:50 - 18:10 Talks: Clustering & Privacy.

    Clustering Algorithms for the Centralized and Local Models of Differential Privacy.
    Uri Stemmer and Kobbi Nissim.
    On Similarity Prediction and Pairwise Clustering.
    Stephen Pasteris, Fabio Vitale, Claudio Gentile and Mark Herbster.
    Smooth Sensitivity Based Approach for Differentially Private Principal Component Analysis.
    Alon Gonen and Ran Gilad-Bachrach.
    Corrupt Bandits for Preserving Local Privacy.
    Pratik Gajane, Tanguy Urvoy and Emilie Kaufmann.

  3. SUN APR 8
  4. 09:00 - 11:00 Tutorial 2

    A Tutorial on Statistical Queries.
    Lev Reyzin.

    11:00 - 11:30 Coffee Break

    11:30 - 13:30 Talks: Statistical Learning

    Learning under p-Tampering Attacks.
    Saeed Mahloujifar, Dimitrios Diochnos and Mohammad Mahmoody.
    Robust Inference for Multiclass Classification.
    Uriel Feige, Yishay Mansour and Robert Schapire.
    Multi-task Kernel Learning Based on Probabilistic Lipschitzness.
    Anastasia Pentina and Shai Ben-David.
    Learning Decision Trees with Stochastic Linear Classifiers.
    Tom Jurgenson and Yishay Mansour.
    Ranking Median Regression: Learning to Order through Local Consensus.
    Anna Korba, Stephan Clemencon and Eric Sibony.
    An Adaptive Strategy for Active Learning with Smooth Decision Boundary.
    Andrea Locatelli, Alexandra Carpentier and Samory Kpotufe.

    13:30 - 14:30 Lunch

    14:30 - 15:00 Business Meeting

    15:00 - 16:20 Talks: Bandit II

    Bandit Regret Scaling with the Effective Loss Range.
    Nicolo Cesa-Bianchi and Ohad Shamir.
    Instrument-Armed Bandits.
    Nathan Kallus.
    Multi-Player Bandits Models Revisited.
    Lilian Besson and Emilie Kaufmann.
    A Better Resource Allocation Algorithm with Semi-Bandit Feedback.
    Yuval Dagan and Koby Crammer.

    16:20 - 16:40 Coffee Break

    16:40 - 17:40 Talks: Other Directions

    Structure Learning of H-colorings.
    Antonio Blanca, Zongchen Chen, Daniel Stefankovic and Eric Vigoda.
    Minimax Rates and Efficient Algorithms for Noisy Sorting.
    Cheng Mao, Jonathan Weed and Philippe Rigollet.
    Adaptive Group Testing Algorithms to Estimate the Number of Defectives.
    Nader Bshouty, Vivian Bshouty-Hurani, George Haddad, Thomas Hashem, Fadi Khoury and Omar Sharafy.

    18:00 - 20:00 Boat Ride

    20:30 - 22:30 Gala Dinner

  5. MON APR 9
  6. 09:00 - 10:00 Invited Talk by Claudio Gentile


    10:00 - 11:00 Talks: Analysis & Generalization

    Dimension-free Information Concentration via Exp-Concavity.
    Ya-Ping Hsieh and Volkan Cevher.
    Unperturbed: spectral analysis beyond Davis-Kahan.
    Justin Eldridge, Mikhail Belkin and Yusu Wang.
    Learners that Use Little Information.
    Raef Bassily, Shay Moran, Ido Nachum, Jonathan Shafer and Amir Yehudayoff.

    11:00 - 11:30 Coffee Break

    11:30 - 13:30 Talks: MDPs, Inductive Inference, Online Learning

    Markov Decision Processes with Continuous Side Information.
    Aditya Modi, Nan Jiang, Satinder Singh and Ambuj Tewari.
    Variance-Aware Regret Bounds for Undiscounted Reinforcement Learning in MDPs.
    Mohammad Sadegh Talebi and Odalric-Ambrym Maillard.
    On the Help of Bounded Shot Verifiers, Comparers, and Standarisers for Learnability in Inductive Inference.
    Ziyuan Gao, Sanjay Jain, Frank Stephan and Thomas Zeugmann.
    Online Learning of Combinatorial Objects via Extended Formulation.
    Holakou Rahmanian, David Helmbold and S.V.N. Vishwanathan.
    Minimax Optimal Bayes Mixtures for Memoryless Sources over Large Alphabets.
    Elias Jaasaari, Janne Leppa-Aho, Tomi Silander and Teemu Roos.
    Sequential prediction with coded side information under logarithmic loss.
    Yanina Shkel, Maxim Raginsky and Sergio Verdu.