2 citations · 6 across the 31 of their papers we have counts for
5 papers · 1 filter
CLS Hardness of 2D Min-Max Optimization with Product Constraints
Alkis Kalavasis, Panagiotis Patsilinakos, Stratis Skoulakis +1
We study the complexity of computing approximate first-order Nash equilibria in min-max optimization problems with one dimensional min and max players and product constraints. For…
On the Learning Curves of Revenue Maximization
Steve Hanneke, Alkis Kalavasis, Shay Moran +1
Learning curves are a fundamental primitive in supervised learning, describing how an algorithm's performance improves with more data and providing a quantitative measure of its ge…
Mean Estimation from Coarse Data: Characterizations and Efficient Algorithms
Alkis Kalavasis, Anay Mehrotra, Manolis Zampetakis +2
Coarse data arise when learners observe only partial information about samples; namely, a set containing the sample rather than its exact value. This occurs naturally through measu…
Linear Regression with Unknown Truncation Beyond Gaussian Features
Alexandros Kouridakis, Anay Mehrotra, Alkis Kalavasis +1
In truncated linear regression, samples are shown only when the outcome falls inside a certain survival set and the goal is to estimate the unknown -dimens…
Learning Mixture Models via Efficient High-dimensional Sparse Fourier Transforms
Alkis Kalavasis, Pravesh K. Kothari, Shuchen Li +1
In this work, we give a time and sample algorithm for efficiently learning the parameters of a mixture of spherical distributions in dimensions. Unlike al…