Machine Learning
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 […]
FDS Colloquium: Xinyi Chen (Princeton University), “Principled Algorithms for Efficient Machine Learning”
Abstract: Machine learning has driven many technological breakthroughs, yet training neural networks has become increasingly expensive. In this talk, I will present my research […]
FDS Colloquium: YJ Choe (University of Chicago), “Topics in sequential anytime-valid inference: Comparing forecasters & combining evidence”
Abstract: Given sequentially observed data, anytime-valid methods guarantee valid inference at arbitrary stopping times, as opposed to pre-specified sample sizes, thereby allowing the experimenter […]
FDS Colloquium: Eran Malach (Harvard), “Learning Hard Problems with Neural Networks and Language Models”
Abstract: Modern machine learning models, and in particular large language models, can now solve surprisingly complex mathematical reasoning problems. In this talk I will […]
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 […]
