3 citations · 6 across the 3 of their papers we have counts for
8 papers
Explicit Lower Bounds Against -Rounds of Sum-of-Squares
Max Hopkins, Ting-Chun Lin
We construct an explicit family of 3-XOR instances hard for -levels of the Sum-of-Squares (SoS) semi-definite programming hierarchy. Not only is this the first explicit const…
Bounded Memory Active Learning through Enriched Queries
Max Hopkins, Daniel Kane, Shachar Lovett +1
The explosive growth of easily-accessible unlabeled data has lead to growing interest in active learning, a paradigm in which data-hungry learning algorithms adaptively select info…
High Dimensional Expanders: Eigenstripping, Pseudorandomness, and Unique Games
Mitali Bafna, Max Hopkins, Tali Kaufman +1
Higher order random walks (HD-walks) on high dimensional expanders (HDX) have seen an incredible amount of study and application since their introduction by Kaufman and Mass [KM16]…
Point Location and Active Learning: Learning Halfspaces Almost Optimally
Max Hopkins, Daniel M. Kane, Shachar Lovett +1
Given a finite set and a binary linear classifier , how many queries of the form are required to learn the label of eve…
Noise-tolerant, Reliable Active Classification with Comparison Queries
Max Hopkins, Daniel Kane, Shachar Lovett +1
With the explosion of massive, widely available unlabeled data in the past years, finding label and time efficient, robust learning algorithms has become ever more important in the…
A Novel CMB Component Separation Method: Hierarchical Generalized Morphological Component Analysis
Sebastian Wagner-Carena, Max Hopkins, Ana Diaz Rivero +1
We present a novel technique for Cosmic Microwave Background (CMB) foreground subtraction based on the framework of blind source separation. Inspired by previous work incorporating…