Machine Learning
S&DS Seminar: Zhuoran Yang (Yale), “Unveiling In-Context Learning: Provable Training Dynamics and Feature Learning in Transformers”
Abstract: In-context learning (ICL) is a cornerstone of large language model (LLM) functionality, yet its theoretical foundations remain elusive due to the complexity of transformer […]
FDS/CADMY Research in Motion Colloquium: Nicolas Stier-Moses (Meta), “Pacing Mechanisms For Ad Auctions”
Research in Motion Series is co-hosted by the Center for Algorithms, Data, and Market Design at Yale (CADMY) and the Yale Institute for Foundations […]
FDS Women’s Career Development Colloquium: Tal Sarig (Meta)
Please join us for the FDS Women’s Career Development Colloquium Series, proudly supported by the Department of Statistics and Data Science (S&DS) and the Yale Institute for […]
FDS/CADMY Research in Motion Colloquium: Aranyak Mehta (Google Research), “From Theory to Practice, and Back: Ad Auctions and Online Matching”
Research in Motion Series is co-hosted by the Center for Algorithms, Data, and Market Design at Yale (CADMY) and the Yale Institute for Foundations […]
S&DS Seminar: Stan Osher (UCLA), “Recent Results on Mean Field Games, Optimal Transport, and In-Context Learning”
Abstract: We have recently been developing algorithms related to mean field games, optimal transport, in-context learning, score based generative models and links between Laplace’s method, […]
Joint ECON/S&DS Training Seminar: Joshua Blumenstock (Berkeley), “Machine Learning to Anticipate Manipulation”
Joint ECON/S&DS Training Seminar: Joshua Blumenstock (Berkeley), “Machine Learning to Anticipate Manipulation” Abstract: An increasing number of decisions are guided by machine learning algorithms. […]
FDS Colloquium: Emma Zang (Yale), “Harnessing AI and Digital Data: Unlocking New Frontiers in Family Research”
Abstract: AI and digital data have been increasingly used to explore a wide range of social science topics, yet their potential in family research […]
S&DS Seminar: Yury Polyanskiy (MIT), “Clustering and phase transitions in transformers”
Abstract: Most of the recent advances in AI are based around a neural architecture known as Transformer. We describe the process of evolution of […]
Optimal Guarantees for Algorithmic Reproducibility and Gradient Complexity in Convex Optimization
Liang Zhang, Junchi Yang, Amin Karbasi, Niao He
Liang Zhang, Junchi Yang, Amin Karbasi, Niao He
Yale Theory Student Seminar: Alkis Kalavasis, “Some Open Problems in TCS”
Abstract: “Overview of the things I am interested in (Machine Learning & Optimization)” Question 1 (TCS): Query Complexity of MaxCut and beyond. Question 2 […]
S&DS Seminar: Mingyuan Zhou (UTexas at Austin), “Score identity Distillation: Exponentially Fast Distillation of Pretrained Diffusion Models for One-Step Generation”
3:30pm – Pre-talk meet and greet teatime – 219 Prospect Street, 13 floor, there will be light snacks and beverages in the kitchen area. […]
Yale Theory Student Seminar: Siddharth Mitra, “On System Identification in Linear Dynamical System”
If you are interested in joining the mailing list, please reach out to Marco Pirazzini (marco.pirazzini@yale.edu) or Siddharth Mitra (siddharth.mitra@yale.edu). Yale Theory Student Seminar […]
Yale Theory Student Seminar: Siddharth Mitra, “On Single–cell Trajectory Inference”
If you are interested in joining the mailing list, please reach out to Marco Pirazzini (marco.pirazzini@yale.edu) or Siddharth Mitra (siddharth.mitra@yale.edu). Yale Theory Student Seminar […]
Yale Theory Student Seminar: Jinzhao Wu, “On the Optimal Fixed–Price Mechanism in Bilateral Trade”
If you are interested in joining the mailing list, please reach out to Marco Pirazzini (marco.pirazzini@yale.edu) or Siddharth Mitra (siddharth.mitra@yale.edu). Yale Theory Student Seminar […]
