ADSI Working Group

Welcome to the page of the ADSI Working Group. If you wish to present at the group, please contact Vincent Roulet.

Meeting time: Fridays at 1:30pm
Meeting location: Variable (location is announced on the mailing list) Organizers: Zaid Harchaoui, Sham Kakade, Maryam Fazel, Kevin Jamieson, John Thickstun
Mailing List: https://mailman.cs.washington.edu/mailman/listinfo/ml-opt

Quarter: Fall 2019

11/15/2019 Mitas Ray, UW
Welfare maximization with production costs: A primal dual approach

11/8/2019 Yue Sun, UW
Escaping saddle on manifold

11/1/2019 Aravind Rajeswaran, UW
Meta Learning with Implicit Gradients. FTML iMAML

10/25/2019 Alec Greaves-Tunnell, UW
Optimal spectral transportation with applications to music transcription

10/11/2019 Zhaoqi Li, UW
LanczosNet: Multi-Scale Deep Graph Convolutional Networks

10/4/2019 Dmitriy Drusvyatskiy, UW
Robust Stochastic Optimization with the Proximal Point Method

9/27/2019 John Thickstun, UW
Deep Learning with Logged Bandit Feedback

Quarter: Spring 2019

6/7/2019
Omid Sadeghi, UW
Controlling Discrimination in Online Auctions

5/31/2019
John Thickstun, UW
Transformer Networks

5/17/2019
Andrew Wagenmaker, UW
Temporal Difference Learning

5/10/2019
Alec Greaves-Tunnell, UW
Long Memory Processes

5/3/2019
Vincent Roulet, UW
Iterative Linearized Control: Stable Algorithms and Complexity Guarantees

4/26/2019
Ross Boczar, Berkeley
Learning to Control in Finite Time

4/19/2019
Greg Yang, Microsoft
Batch Normalization Causes Gradient Explosion

Quarter: Winter 2019

3/15/2019
Omid Sadeghi, UW
Online convex optimization for cumulative constraints

3/8/2019
Lillian Ratliff, UW
Learning in Non-Stationary Environments: Near-Optimal Guarantees

3/1/2019
Corinne Jones, UW
Deriving Neural Architectures from Kernels

2/22/2019
Ramya Vinayak, UW
MLE for Learning Populations of Parameters

2/15/2019
Lang Liu, UW
Optimization Guarantees for Overparameterized Nets

2/1/2019
Krishna Pillutla, UW
Localized Structured Prediction

Quarter: Fall 2018

11/30/2018
Gang Cheng, UW
Certificates for approximately correct clustering

11/16/2018
John Thickstun, UW
Generative Modeling with Sinkhorn Divergences

11/2/2018
Yue Sun, UW
Learning Linear Dynamical Systems

10/26/2018 Aravind Rajeswaran, UW
TBA

10/12/2018
Ashok Vardhan, UIUC
Globally Consistent Algorithms for Mixture of Experts

10/5/2018
Romain Camilleri, UW
Imitation Learning and DAGGER

Quarter: Summer 2018

7/20/2018
Weihao Kong, Stanford
Estimating unexplained variance and learnability in the sublinear data regime

Quarter: Spring 2018

6/8/2018
Vincent Roulet, UW
Grouping Features for Prediction

6/1/2018
Krishna Pillutla, UW
Regularization for Structured Prediction

5/25/2018
Fabian Pedregosa, Berkeley
Asynchronous Stochastic Optimization

5/11/2018
Mathurin Massias, Télécom ParisTech
Celer: dual extrapolation for faster Lasso solvers

5/4/2018
Omid Sadeghi, UW
Fast Algorithms for Online Stochastic Convex Programming

4/27/2018
Rahul Kidambi, UW
Evaluating predictions on selectively labeled data

4/20/2018
Nadav Cohen, Princeton
Implicit Acceleration by Overparameterization

4/6/2018
Dmitriy Drusvyatskiy, UW
SGD rate for weakly convex functions

3/30/2018
Chi Jin, Berkeley
Nonconvex optimization: acceleration, saddle points, and shallow minima

Quarter: Winter 2018

1/26/2018
Jennifer Rogers, Aravind Rajeswaran, UW
Adversarial Examples and Robust Optimization

2/16/2018
Krishna Pillutla, UW
Consistency for Structured Prediction

1/26/2018
Ramya Vinayak, UW
Learning Populations of Parameters

1/19/2018
Alec Greaves-Tunnell, UW
Learning Overcomplete HMMs

1/12/2018
Yue Sun, UW
Accelerated gradient methods on non-convex loss surfaces

1/5/2018
Jerry Li, MIT
Robust Estimation

Quarter: Fall 2017

11/17/2017
Swati Padmanabhan, UW
Deterministic Approximate Caratheodory

11/3/2017
Krishna Pillutla, UW
Dualing GANs

10/27/2017
Jennifer Rogers, UW
Intelligible Models (paper1 , paper2)

10/13/2017
Aravind Rajeswaran, UW
Model Agnostic Meta Learning

10/6/2017
Chris Xie, UW
Visual Object Tracking

Past Quarters