learning algorithm

Achieving Fairness in the Stochastic Multi-Armed Bandit Problem AAAI 2020 A Non-Trivial Algorithm Enumerating Relevant Features over Finite Fields ALT 2020 AutoML-Zero: Evolving Machine Learning Algorithms From Scratch ICML 2020 Optimally Deceiving a Learning Leader in Stackelberg Games NeurIPS 2020 Average-Case Information Complexity of Learning ALT 2019 Critical Percolation as a Framework to Analyze the Training of Deep Networks ICLR 2018 Effective Parallelisation for Machine Learning NeurIPS 2017 Fairness in Reinforcement Learning ICML 2017 Information-theoretic analysis of generalization capability of learning algorithms NeurIPS 2017 Nearest-Neighbor Sample Compression: Efficiency, Consistency, Infinite Dimensions NeurIPS 2017 A Guide to Learning Arithmetic Circuits COLT 2016 Learning Algorithms for Second-Price Auctions with Reserve JMLR 2016 Learning in Games: Robustness of Fast Convergence NeurIPS 2016 Search Improves Label for Active Learning NeurIPS 2016 Links Between Multiplicity Automata, Observable Operator Models and Predictive State Representations -- a Unified Learning Framework JMLR 2015 Exploiting easy data in online optimization NeurIPS 2014 Learning Theory and Algorithms for revenue optimization in second price auctions with reserve ICML 2014 Near-Optimal Density Estimation in Near-Linear Time Using Variable-Width Histograms NeurIPS 2014 Optimal Regret Minimization in Posted-Price Auctions with Strategic Buyers NeurIPS 2014 Competing With Strategies COLT 2013 Interpreting prediction markets: a stochastic approach NeurIPS 2012 No-Regret Algorithms for Unconstrained Online Convex Optimization NeurIPS 2012 Practical Bayesian Optimization of Machine Learning Algorithms NeurIPS 2012 Using More Data to Speed-up Training Time AISTATS 2012 Minimax Regret of Finite Partial-Monitoring Games in Stochastic Environments COLT 2011