Machine Learning Group Seminar (Fall 2020)

Time: 2:30PM - 5:00PM CST, Friday, Online: Zoom link

Hosted by: Tianbao Yang, Qihang Lin, Peng Jiang

Topic: The general topics of interest is machine learning and optimization. In particular, we are interested in stochastic optimization, non-convex optimization, constrained optimization, efficient methods for large-scale training of deep neural networks, etc.

Recommended Papers: Reading Lists of Machine Learning Group Seminar (Fall 2020)

Maintained by: Qi Qi

Week Date Topic Presenter Recorded Videos
1 Sep 4, 2020 DropoutNet: Addressing Cold Start in Recommender Systems Dixian Zhu Password Required
2 Sep 11, 2020 Nesterov's Method with Decreasing Learning Rate Leads to Accelerated Stochastic Gradient Descent Yan Yan Password Required
3 Sep 18, 2020 Distance Encoding – Design Provably More Powerful Graph Neural Networks for Structural Representation Learning Xin Man Password Required
4 Sep 25, 2020 SCAFFOLD: Stochastic Controlled Averaging for Federated Learning Zhishuai Guo Password Required
5 Oct 2, 2020 Complexity of Finding Stationary Points of Nonsmooth Nonconvex Functions Yankun Huang Password Required
6 Oct 9, 2020 Minimal Variance Sampling with Provable Guarantees for Fast Training of Graph Neural Networks Masuma Akter Rumi Password Required
7 Oct 16, 2020 Optimal Accelerated Variance Reduced EXTRA and DIGing for Strongly Convex and Smooth Decentralized Qi Qi Password Required
8 Oct 23, 2020 Canceled
9 Oct 30, 2020 A Simple Framework for Contrastive Learning of Visual Representations Zhuoning Yuan Password Required
10 Nov 6, 2020 ROOT-SGD: Sharp Nonasymptotics and Asymptotic Efficiency in a Single Algorithm Qi Qi
11 Nov 13, 2020 Canceled
12 Nov 20, 2020 Variational Inference: A Review for Statisticians Dixian Zhu
13 Nov 27, 2020 Thanksgiving Break Happy Thanksgiving!
14 Dec 4, 2020 Optimal Algorithms for Convex Nested Stochastic Composite Optimization Qi Qi
15 Dec 11, 2020 Final Exam Week