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20042022
most citedFeUdal Networks for Hierarchical Reinforcement Learning

252 citations

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14 papers · 1 filter

cs.LG2018★ 1 cited

Contextual Memory Trees

Wen Sun, Alina Beygelzimer, Hal Daumé +2

We design and study a Contextual Memory Tree (CMT), a learning memory controller that inserts new memories into an experience store of unbounded size. It is designed to efficiently…

cs.LG2018★ 103 cited

A Reductions Approach to Fair Classification

Alekh Agarwal, Alina Beygelzimer, Miroslav Dudík +2

We present a systematic approach for achieving fairness in a binary classification setting. While we focus on two well-known quantitative definitions of fairness, our approach enco…

cs.LG2016★ 3 cited

Distributed Flexible Nonlinear Tensor Factorization

Shandian Zhe, Kai Zhang, Pengyuan Wang +4

Tensor factorization is a powerful tool to analyse multi-way data. Compared with traditional multi-linear methods, nonlinear tensor factorization models are capable of capturing mo…

cs.LG2016★ 1 cited

Geometry Aware Mappings for High Dimensional Sparse Factors

Avradeep Bhowmik, Nathan Liu, Erheng Zhong +2

While matrix factorisation models are ubiquitous in large scale recommendation and search, real time application of such models requires inner product computations over an intracta…

cs.LG2016

Online Sparse Linear Regression

Dean Foster, Satyen Kale, Howard Karloff

We consider the online sparse linear regression problem, which is the problem of sequentially making predictions observing only a limited number of features in each round, to minim…

cs.LG2016★ 16 cited

Coin Betting and Parameter-Free Online Learning

Francesco Orabona, Dávid Pál

In the recent years, a number of parameter-free algorithms have been developed for online linear optimization over Hilbert spaces and for learning with expert advice. These algorit…