
Machine Learning
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
Other Videos By Simons Institute for the Theory of Computing
2021-01-15 | Algorithmic Persuasion with Evidence |
2021-01-15 | Comparing computational entropies below majority (or: When is the dense model theorem false?) |
2021-01-15 | The entropy of lies: playing twenty questions with a liar |
2021-01-12 | Error Correcting Codes for Uncompressed Messages |
2021-01-12 | Algorithms and Hardness for Multidimensional Range Updates and Queries |
2021-01-12 | Algebraic and circuit complexity |
2021-01-12 | Online and streaming algorithms |
2021-01-12 | Algorithmic Game Theory |
2021-01-12 | Optimization |
2021-01-12 | Codes and information |
2021-01-12 | Machine Learning |
2021-01-11 | Circuits and communication |
2021-01-10 | Graph algorithms |
2021-01-10 | Algorithms |
2021-01-10 | GRADUATING BITS |
2021-01-10 | Algorithmic game theory |
2021-01-10 | Quantum information |
2021-01-10 | Quantum |
2021-01-09 | Analytic methods |
2021-01-09 | Computational complexity |
2021-01-08 | Distributed models |