ALT 2018

33 papers

A Better Resource Allocation Algorithm with Semi-Bandit Feedback Yuval Dagan, Crammer Koby

Adaptive Group Testing Algorithms to Estimate the Number of Defectives Nader H. Bshouty, Vivian E. Bshouty-Hurani, George Haddad, Thomas Hashem, Fadi Khoury, Omar Sharafy

An Adaptive Strategy for Active Learning with Smooth Decision Boundary Andrea Locatelli, Alexandra Carpentier, Samory Kpotufe

Bandit Regret Scaling with the Effective Loss Range Nicolò Cesa-Bianchi, Ohad Shamir

Clustering Algorithms for the Centralized and Local Models Kobbi Nissim, Uri Stemmer

Convergence of Langevin MCMC in KL-Divergence Xiang Cheng, Peter Bartlett

Coordinate Descent Faceoff: Primal or Dual? Dominik Csiba, Peter Richtárik

Corrupt Bandits for Preserving Local Privacy Pratik Gajane, Tanguy Urvoy, Emilie Kaufmann

Decision Making with Limited Feedback Danielle Ensign, Frielder Sorelle, Neville Scott, Scheidegger Carlos, Venkatasubramanian Suresh

Dimension-Free Information Concentration via Exp-Concavity Ya-ping Hsieh, Volkan Cevher

Efficient Coordinate-Wise Leading Eigenvector Computation Jialei Wang, Weiran Wang, Dan Garber, Nathan Srebro

Instrument-Armed Bandits Nathan Kallus

Learners That Use Little Information Raef Bassily, Shay Moran, Ido Nachum, Jonathan Shafer, Amir Yehudayoff

Learning Decision Trees with Stochastic Linear Classifiers Tom Jurgenson, Yishay Mansour

Learning Under $p$-Tampering Attacks Saeed Mahloujifar, Dimitrios I. Diochnos, Mohammad Mahmoody

Markov Decision Processes with Continuous Side Information Aditya Modi, Nan Jiang, Satinder Singh, Ambuj Tewari

Minimax Optimal Bayes Mixtures for Memoryless Sources over Large Alphabets Elias Jääsaari, Janne Leppä-aho, Tomi Silander, Teemu Roos

Minimax Rates and Efficient Algorithms for Noisy Sorting Cheng Mao, Jonathan Weed, Philippe Rigollet

Multi-Player Bandits Revisited Lilian Besson, Emilie Kaufmann

Multi-Task Kernel Learning Based on Probabilistic Lipschitzness Anastasia Pentina, Shai Ben-David

On Similarity Prediction and Pairwise Clustering Stephen Pasteris, Fabio Vitale, Claudio Gentile, Mark Herbster

On the Help of Bounded Shot Verifiers, Comparators and Standardisers for Learnability in Inductive Inference Ziyuan Gao, Sanjay Jain, Frank Stephan, Thomas Zeugmann

Online Learning of Combinatorial Objects via Extended Formulation Holakou Rahmanian, David P. Helmbold, S. V. N. Vishwanathan

Pure Exploration in Infinitely-Armed Bandit Models with Fixed-Confidence Maryam Aziz, Jesse Anderton, Emilie Kaufmann, Javed Aslam

Ranking Median Regression: Learning to Order Through Local Consensus Stephan Clémençon, Anna Korba, Eric Sibony

Robust Inference for Multiclass Classification Uriel Feige, Yishay Mansour, Robert E. Schapire

Sequential Prediction with Coded Side Information Under Logarithmic Loss Yanina Shkel, Maxim Raginsky, Sergio Verdú

Smooth Sensitivity Based Approach for Differentially Private PCA Alon Gonem, Ram Gilad-Bachrach

Sparsity, Variance and Curvature in Multi-Armed Bandits Sébastien Bubeck, Michael Cohen, Yuanzhi Li

Structure Learning of ${h}$-Colorings Antonio Blanca, Zongchen Chen, Daniel Štefankovič, Eric Vigoda

The K-Nearest Neighbour UCB Algorithm for Multi-Armed Bandits with Covariates Henry Reeve, Joe Mellor, Gavin Brown

Unperturbed: Spectral Analysis Beyond Davis-Kahan Justin Eldridge, Mikhail Belkin, Yusu Wang

Variance-Aware Regret Bounds for Undiscounted Reinforcement Learning in MDPs Mohammad Sadegh Talebi, Odalric-Ambrym Maillard