88 citations · 311 across the 59 of their papers we have counts for
6 papers · 1 filter
Agnostically Learning Multi-index Models with Queries
Ilias Diakonikolas, Daniel M. Kane, Vasilis Kontonis +2
We study the power of query access for the task of agnostic learning under the Gaussian distribution. In the agnostic model, no assumptions are made on the labels and the goal is t…
Optimizing Solution-Samplers for Combinatorial Problems: The Landscape of Policy-Gradient Methods
Constantine Caramanis, Dimitris Fotakis, Alkis Kalavasis +2
Deep Neural Networks and Reinforcement Learning methods have empirically shown great promise in tackling challenging combinatorial problems. In those methods a deep neural network…
Distribution-Independent Regression for Generalized Linear Models with Oblivious Corruptions
Ilias Diakonikolas, Sushrut Karmalkar, Jongho Park +1
We demonstrate the first algorithms for the problem of regression for generalized linear models (GLMs) in the presence of additive oblivious noise. We assume we have sample access…
Self-Directed Linear Classification
Ilias Diakonikolas, Vasilis Kontonis, Christos Tzamos +1
In online classification, a learner is presented with a sequence of examples and aims to predict their labels in an online fashion so as to minimize the total number of mistakes. I…
Buying Information for Stochastic Optimization
Mingchen Ma, Christos Tzamos
Stochastic optimization is one of the central problems in Machine Learning and Theoretical Computer Science. In the standard model, the algorithm is given a fixed distribution know…
Weitzman's Rule for Pandora's Box with Correlations
Evangelia Gergatsouli, Christos Tzamos
Pandora's Box is a central problem in decision making under uncertainty that can model various real life scenarios. In this problem we are given boxes, each with a fixed openin…