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When Wednesday July 24th 10:00am *Updated Where: HDSI 123 * Updated Zoom Info: https://ucsd.zoom.us/j/99334315002 *Updated Title: What Kinds of Functions do Neural Networks Learn? Theory and Practical Applications Abstract: This talk presents a theory characterizing […]
The Halıcıoğlu Data Science Institute (HDSI) at UC San Diego is excited to welcome all employers, partners, campus colleagues, and the broader community to our 2024 Virtual Industry Open House. […]
The UC San Diego EnCORE is excited to host Industry Day on Wednesday, September 4th, 2024, at the UCSD campus. This all-day event will showcase exciting research in foundations of data […]
Join us for a special celebration in honor of Karandeep Singh, MD, the Joan and Irwin Jacobs Chancellor’s Endowed Chair in Digital Health Innovation. In addition to this prestigious role, […]
Talk Abstract Cities, humanity’s greatest inventions, offer vast opportunities for innovation in science and technology. The increasing availability of big data paints a promising future for our cities. Over the […]
Beyond their use in traditional data analytics problems, AI and Machine Learning techniques are changing the way real-world complex systems (like vehicles, airplanes, and even industrial production lines) are designed, […]
Talk Information: When Monday Oct 21st 1:00pm Where: HDSI MPR 123 Zoom Info: http://bit.ly/HDSI-Seminars Title: Generative Social Choice Abstract: "The mathematical study of voting, social choice theory, has traditionally only been applicable to choices among a few […]
ABSTRACT The advent of deep learning has completely revolutionized how we perceive data to obtain superhuman performance across all fields of modern science. However, despite the remarkable empirical successes of […]
Talk Information: When Wednesday Oct 30th 1:00pm Where: HDSI MPR 123 Zoom Info: http://bit.ly/HDSI-Seminars Title: Modeling and Inference of Complementarity Mechanisms in Networks. Abstract: "In many networks, including networks of protein-protein interactions, […]
Title: Revisiting Scalarization in Multi-Task Learning Abstract: Linear scalarization, i.e., combining all loss functions by a weighted sum, has been the default choice in the literature of multi-task learning (MTL) since its […]
