Fall 2019

September 18, 2019

Convex Relaxation of Combined Heat and Power Dispatch

Speaker: Yibao Jiang (LIDS)

Combined heat and power dispatch are utilized for coordinated scheduling of electric power systems and district heating systems via interactions through combined heat and power plants and heat pumps. Nonlinear heating flow models generally...

September 25, 2019

Bounding Machine Learning Model Errors in Power Grid Analysis

Speaker: Yuxiao Liu (LIDS)

Machine learning methods analysis power grids under incomplete physical information, and their accuracy has been mostly validated empirically using excessive testing datasets. We explore error bounds for machine learning methods under all...

October 2, 2019

Efficient Learning from Untrusted Batches

Speaker: Sitan Chen (CSAIL)

In recent years there has been an explosion of interest in designing unsupervised learning algorithms able to tolerate adversarial corruptions in the input data. A notable instantiation of this, first introduced to the theory community by...

October 9, 2019

Genomic Variety Estimation via Bayesian Nonparametrics

Speaker: Lorenzo Masoero (EECS)

The exponential growth in size of human genomic studies, with tens of thousands of observations,  opens up the intriguing possibility to investigate the role of rare genetic variants in biological human evolution. A better understanding of...

October 16, 2019

Learning L2 Continuous Regression Functionals via Regularized Riesz Representers

Speaker: Rahul Singh (Economics)

Many objects of interest can be expressed as an L2 continuous functional of regression, including average treatment effects, economic average consumer surplus, expected conditional covariances, and discrete choice parameters that depend on...

October 23, 2019

LR-GLM: High-Dimensional Bayesian Inference Using Low Rank Data Approximations

Speaker: Brian Trippe (CSAIL)

Due to the ease of modern data collection, practitioners often have access to a large set of covariates that they wish to relate to some observed outcome. Generalized linear models (GLMs) offer a particularly interpretable framework for such...

October 30, 2019

Randomized Control Meets Synthetic Control

Speaker: Anish Agrawal (LIDS)

Consider the setting where there are N units and I interventions (i.e., treatments) of interest. The aim is to find the best-personalized intervention for each unit. When the units are homogenous, the randomized control trial (RCT) framework...

November 6, 2019

The Distributed Setup, Some Definitions and Problem Statements

Speaker: Cesar A Uribe (LIDS)

Cesar will show some recent results on the study of the optimal convergence rates for distributed convex optimization problems over networks, where the objective is to minimize a sum of local functions of the nodes in the network. We provide...

November 13, 2019

WiFresh: Age-of-Information from Theory to Implementation

Speaker: Igor Kadota (LIDS)

Emerging applications, such as autonomous vehicles and smart factories, increasingly rely on sharing time-sensitive information for monitoring and control. In such application domains, it is essential to keep information fresh, as outdated...

November 20, 2019

Learning an Unknown Network State in Congestion Games

Speaker: Manxi Wu (IDSS)

We study learning dynamics induced by myopic players who repeatedly play a congestion game on a network with an unknown state. The state impacts the cost functions of one or more edges of the network. In each stage, players choose...

December 4, 2019

Permutation-Based Causal Structure Learning from Interventional Data with Unknown Targets

Speaker: Chandler Squires (LIDS)

Recent innovations in gene editing and gene sequencing technologies have opened the door to developing a more complete understanding of gene regulatory networks, with applications for disease diagnosis, drug development, and biochemical...