output
20092026
most citedImproving fairness in machine learning systems: What do industry practitioners need?

758 citations

researchers with a paper here

Counting papers with at most 25 authors, so collaboration author lists do not stand in for the people here.

collaborating institutions
Showing 2014Show all

7 papers · 1 filter

stat.ML2014★ 44 cited

A Lower Bound for the Optimization of Finite Sums

Alekh Agarwal, Leon Bottou

This paper presents a lower bound for optimizing a finite sum of functions, where each function is -smooth and the sum is -strongly convex. We show that no algorithm can…

cs.SI2014★ 103 cited

Processing Social Media Messages in Mass Emergency: A Survey

Muhammad Imran, Carlos Castillo, Fernando Diaz +1

Social media platforms provide active communication channels during mass convergence and emergency events such as disasters caused by natural hazards. As a result, first responders…

cs.LG2014★ 43 cited

Logarithmic Time Online Multiclass prediction

Anna Choromanska, John Langford

We study the problem of multiclass classification with an extremely large number of classes (k), with the goal of obtaining train and test time complexity logarithmic in the number…

cs.DS2014★ 6 cited

Adaptive Contract Design for Crowdsourcing Markets: Bandit Algorithms for Repeated Principal-Agent Problems

Chien-Ju Ho, Aleksandrs Slivkins, Jennifer Wortman Vaughan

Crowdsourcing markets have emerged as a popular platform for matching available workers with tasks to complete. The payment for a particular task is typically set by the task's req…

q-fin.PR2014★ 18 cited

Inside Money, Procyclical Leverage, and Banking Catastrophes

Charles D. Brummitt, Rajiv Sethi, Duncan J. Watts

We explore a model of the interaction between banks and outside investors in which the ability of banks to issue inside money (short-term liabilities believed to be convertible int…

cs.AI2014★ 3 cited

Information Aggregation in Exponential Family Markets

Jacob Abernethy, Sindhu Kutty, Sébastien Lahaie +1

We consider the design of prediction market mechanisms known as automated market makers. We show that we can design these mechanisms via the mold of \emph{exponential family distri…

cs.LG2014★ 289 cited

Taming the Monster: A Fast and Simple Algorithm for Contextual Bandits

Alekh Agarwal, Daniel Hsu, Satyen Kale +3

We present a new algorithm for the contextual bandit learning problem, where the learner repeatedly takes one of actions in response to the observed context, and observes the r…