106 citations · 996 across the 72 of their papers we have counts for
4 papers · 1 filter
Efficient Online Portfolio with Logarithmic Regret
Haipeng Luo, Chen-Yu Wei, Kai Zheng
We study the decades-old problem of online portfolio management and propose the first algorithm with logarithmic regret that is not based on Cover's Universal Portfolio algorithm a…
Practical Contextual Bandits with Regression Oracles
Dylan J. Foster, Alekh Agarwal, Miroslav Dudík +2
A major challenge in contextual bandits is to design general-purpose algorithms that are both practically useful and theoretically well-founded. We present a new technique that has…
Logistic Regression: The Importance of Being Improper
Dylan J. Foster, Satyen Kale, Haipeng Luo +2
Learning linear predictors with the logistic loss---both in stochastic and online settings---is a fundamental task in machine learning and statistics, with direct connections to cl…
More Adaptive Algorithms for Adversarial Bandits
Chen-Yu Wei, Haipeng Luo
We develop a novel and generic algorithm for the adversarial multi-armed bandit problem (or more generally the combinatorial semi-bandit problem). When instantiated differently, ou…