Poster session
in
Workshop: OPT 2021: Optimization for Machine Learning
Poster Session 2 (gather.town)
Wenjie Li · Akhilesh Soni · Jinwuk Seok · Jianhao Ma · Jeffery Kline · Mathieu Tuli · Miaolan Xie · Robert Gower · Quanqi Hu · Matteo Cacciola · Yuanlu Bai · Boyue Li · Wenhao Zhan · Shentong Mo · Junhyung Lyle Kim · Sajad Fathi Hafshejani · Chris Junchi Li · Zhishuai Guo · Harshvardhan Harshvardhan · Neha Wadia · Tatjana Chavdarova · Difan Zou · Zixiang Chen · Aman Gupta · Jacques Chen · Betty Shea · Benoit Dherin · Aleksandr Beznosikov
Please join us in gather.town (see link above). To see the abstracts of the posters presented in this session, please see below the schedule.
Authors/papers presenting posters in gather.town for this session:
Optimum-statistical Collaboration Towards Efficient Black-box Optimization, Wenjie Li
Integer Programming Approaches To Subspace Clustering With Missing Data, Akhilesh Soni
Stochastic Learning Equation using Monotone Increasing Resolution of Quantization, Jinwuk Seok
Sign-RIP: A Robust Restricted Isometry Property for Low-rank Matrix Recovery, Jianhao Ma
Farkas' Theorem of the Alternative for Prior Knowledge in Deep Networks, Jeffery Kline
Towards Robust and Automatic Hyper-Parameter Tunning, Mahdi S. Hosseini
High Probability Step Size Lower Bound for Adaptive Stochastic Optimization, Miaolan Xie
Stochastic Polyak Stepsize with a Moving Target, Robert M Gower
A Stochastic Momentum Method for Min-max Bilevel Optimization, Quanqi Hu
Deep Neural Networks pruning via the Structured Perspective Regularization, Matteo Cacciola
Efficient Calibration of Multi-Agent Market Simulators from Time Series with Bayesian Optimization, Yuanlu Bai
DESTRESS: Computation-Optimal and Communication-Efficient Decentralized Nonconvex Finite-Sum Optimization, Boyue Li
Policy Mirror Descent for Regularized RL: A Generalized Framework with Linear Convergence, Shicong Cen
Simulated Annealing for Neural Architecture Search, Shentong Mo
Acceleration and Stability of Stochastic Proximal Point Algorithm, Junhyung Lyle Kim
Barzilai and Borwein conjugate gradient method equipped with a non-monotone line search technique, Sajad Fathi Hafshejani
On the convergence of stochastic extragradient for bilinear games using restarted iteration averaging, Chris Junchi Li
Practice-Consistent Analysis of Adam-Style Methods, Zhishuai Guo
Escaping Local Minima With Stochastic Noise, Harsh Vardhan
Optimization with Adaptive Step Size Selection from a Dynamical Systems Perspective, Neha S Wadia
Last-Iterate Convergence of Saddle Point Optimizers via High-Resolution Differential Equations, Tatjana Chavdarova
Understanding the Generalization of Adam in Learning Neural Networks with Proper Regularization, Difan Zou
Faster Perturbed Stochastic Gradient Methods for Finding Local Minima, Zixiang Chen
Adam vs. SGD: Closing the generalization gap on image classification, Aman Gupta
Heavy-tailed noise does not explain the gap between SGD and Adam on Transformers, Frederik Kunstner
Faster Quasi-Newton Methods for Linear Composition Problems, Betty Shea
The Geometric Occam Razor Implicit in Deep Learning, Benoit Dherin
Random-reshuffled SARAH does not need a full gradient computations, Aleksandr Beznosikov