Events
Upcoming Events
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Past Events
CSE DSI Machine Learning Seminar with Aldo Scutari (IE, Purdue)
Tuesday, Nov. 14, 2023, 11 a.m. through Tuesday, Nov. 14, 2023, Noon
Keller Hall 3-180 and via Zoom.
Aldo Scutari, Purdue University, will give a talk entitled Statistical Inference over Networks: Decentralized Optimization Meets High-Dimensional Statistics.
CSE DSI Machine Learning Seminar with Qing Qu (University of Michigan)
Tuesday, Nov. 7, 2023, 11 a.m. through Tuesday, Nov. 7, 2023, Noon
Keller Hall 3-180 or Zoom
Qing Qu, assistant professor at the University of Michigan, will give a presentation entitled On the Emergence of Invariant Low-Dimensional Subspaces in Gradient Descent for Learning Deep Networks.
IMA Data Science seminar - Data Driven Modeling of Unknown Systems with Deep Neural Networks
Tuesday, Oct. 31, 2023, 1:25 p.m. through Tuesday, Oct. 31, 2023, 2:25 p.m.
Lind Hall 325 and Zoom
Dongbin Xiu (The Ohio State University) will give a talk entitled Data Driven Modeling of Unknown Systems.
CSE DSI Machine Learning Seminar with Volkan Cevher (EPFL)
Tuesday, Oct. 31, 2023, 11 a.m. through Tuesday, Oct. 31, 2023, Noon
Via Zoom. Can be viewed in Keller 3-180.
Volkan Cevher (EPFL) will give a talk entitled Key Challenges in Foundation Models (... and some solutions!).
CRAY Colloquium: Well-being, AI, and You: Developing AI-based Technology to Enhance our Well-being
Monday, Oct. 30, 2023, 11:15 a.m. through Monday, Oct. 30, 2023, 12:15 p.m.
Keller Hall 3-210
Alon Halevy (Meta) will give a talk entitled Well-being, AI, and You: Developing AI-based Technology to Enhance our Well-being.
IMA Data Science Seminar - Trading off accuracy for reduced computation in scientific computing
Tuesday, Oct. 24, 2023, 1:25 p.m. through Tuesday, Oct. 24, 2023, 2:25 p.m.
Lind Hall 325 or via Zoom
Data Science Seminar
Alex Gittens (Rensselaer Polytechnic Institute)
Abstract
Classical linear algebraic algorithms guarantee high accuracy in exchange for high computational cost. These costs can be infeasible in modern applications, so over the last two decades, randomized algorithms have been developed that allow a user-specified trade-off between accuracy and computational efficiency when dealing with massive data sets. The intuition is that when dealing with an excess of structured data (e.g., a large matrix which has low numerical rank), one can toss away a large portion of this data, thereby reducing the computational load, without introducing much additional error into the computation. In this talk we look at the design and performance analysis of several numerical linear algebra and machine learning algorithms--- including linear solvers, approximate kernel machines, and tensor low-rank decomposition--- based upon this principle.
CSE DSI Machine Learning Seminar with Benjamin Grimmer (John Hopkins)
Tuesday, Oct. 24, 2023, 11 a.m. through Tuesday, Oct. 24, 2023, Noon
Keller Hall 3-180 or Zoom.
Benjamin Grimmer will give a talk entitled Accelerated Gradient Descent via Long Steps.
CSE DSI Machine Learning Seminar with Ahmet Alacaoglu (UW-Madison)
Tuesday, Oct. 10, 2023, 11 a.m. through Tuesday, Oct. 10, 2023, Noon
Keller 3-180 or via Zoom.
Ahmet Alacaoglu, UW-Madison, will give a talk entitled Stochastic Variance Reduction Beyond Minimization Problems.
CSE DSI Machine Learning Seminar with Hanshen Xiao (CSAIL, MIT)
Tuesday, Oct. 3, 2023, 11 a.m. through Tuesday, Oct. 3, 2023, Noon
Via Zoom and can be viewed in Keller 3-180.
Hanshen Xiao, CSAIL, MIT, will give a talk entitled PAC Privacy: Automatic Privacy Measurement and Control of Data Processing.
CSE DSI Machine Learning Seminar with Qianwen Wang
Tuesday, Sept. 26, 2023, 11 a.m. through Tuesday, Sept. 26, 2023, Noon
Keller Hall 3-180 and via Zoom.
Qianwen Wang (CS&E, UMN) will give a talk entitled Interpreting and Steering AI Explanations with Interactive Visualizations.