3 papers
cs.LG2023
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…
cs.LG2023
Learning Hard-Constrained Models with One Sample
Andreas Galanis, Alkis Kalavasis, Anthimos Vardis Kandiros
We consider the problem of estimating the parameters of a Markov Random Field with hard-constraints using a single sample. As our main running examples, we use the -SAT and the…
cs.LG2023
Statistical Indistinguishability of Learning Algorithms
Alkis Kalavasis, Amin Karbasi, Shay Moran +1
When two different parties use the same learning rule on their own data, how can we test whether the distributions of the two outcomes are similar? In this paper, we study the simi…