Machine Learning

Machine Learning

Published on ● Video Link: https://www.youtube.com/watch?v=tovZVNz3gd0



Duration: 1:06:07
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Dynamic inference in probabilistic graphical models
Weiming Feng (Nanjing University), Kun He (Shenzhen University, SICS), Xiaoming Sun (ICT,CAS), Yitong Yin (Nanjing University)

Interactive Proofs for Verifying Machine Learning
Jonathan Shafer (UC Berkeley), Guy N. Rothblum (Weizmann Institute of Science), Shafi Goldwasser (UC Berkeley), Amir Yehudayoff (Technion-IIT)

Training (Overparametrized) Neural Networks in Near-Linear Time
Binghui Peng (Columbia University), Zhao Song (Princeton), Jan van den Brand (KTH Royal Institute of Technology), Omri Weinstein (Columbia University)

Counterexamples to the Low-Degree Conjecture
Justin Holmgren (NTT Research), Alexander S. Wein (Courant Institute, NYU)

Tight Hardness Results for Training Depth-2 ReLU Networks
Daniel Reichman (WPI), Pasin Manurangsi (Google Research), Subhi Goel (University of Texas at Austin), Adam R. Klivans (University of Texas at Austin)

ITCS 2021







Tags:
Simons Institute
theoretical computer science
UC Berkeley
Computer Science
Theory of Computation
Theory of Computing
ITCS 2021