October 4, 2023
Kwangjun Ahn (LIDS)
n this talk, I'll be talking about interesting phenomena arising in Deep Learning optimization. In particular, based on a simple yet canonical model, we will discuss how the neural networks learn the "correct" classifiers. Surprisingly,...
October 24, 2023
Guangchun (Grant) Ruan (LIDS)
The performance and service life of electric vehicle (EV) batteries degrade deadly in cold climate, and heating is a common-but-expensive option to survive EVs in this case. Coordinating the heating and charging demand at scale has great potential...
October 25, 2023
Behrooz Tahmasebi (CSAIL)
Group-invariant probability distributions appear in many data-generative models in machine learning, such as graphs, point clouds, and images. In practice, one often needs to estimate divergences between such distributions. In this work, we study...
October 2, 2024
Swati Padmanabhan (LIDS, IDSS)
"Some recent theoretical results in algorithms for nonconvex optimization"
In this talk, we present some recent results on the theoretical guarantees for nonconvex optimization. We will first briefly describe first-order algorithms for attaining...
October 9, 2024
Jiachun Li (LIDS, IDSS)
“The Power of Adaptivity in Experimental Design”
Given experiment subjects with potentially heterogeneous covariates and two possible treatments, namely active treatment and control, our work quantifies the optimal accuracy in estimating the...
October 16, 2024
Yassir Jedra (LIDS)
“Exploiting Observation Bias to Improve Matrix Completion”
We consider a variant of matrix completion where entries are revealed in a biased manner. Our aim is to address the extent to which such bias can be exploited in improving predictions....
November 13, 2024
Prem Talwai (LIDS, ORC)
“Nonparametric Regression in Dirichlet Spaces: A Random Obstacle Approach”
In this paper, we consider nonparametric estimation over general Dirichlet metric measure spaces. Unlike the more commonly studied reproducing kernel Hilbert space, whose...
November 20, 2024
Yuexing Hao (EECS, LIDS)
"Objective Approaches in a Subjective Medical World"
In today’s healthcare system, patients often feel disconnected from clinical professionals and their care journey. They receive a “one-size-fits-all” plan and are left out of the decision-making...
March 12, 2025
Julie Zhu AND Oliver Wang (LIDS)
"Conformal Prediction under Lévy-Prokhorov Distribution Shifts: Robustness to Local and Global Perturbations"
Conformal prediction provides a powerful framework for constructing prediction intervals with finite-sample guarantees, yet its robustness...
May 7, 2025
Eric Weine (LIDS / DFCI)
"A new family of Poisson non-negative matrix factorization models using the shifted log link function"
Non-negative matrix factorization (NMF) is a widely used method to find interpretable, parts-based decompositions of count data. Despite its wide...
