The workshop will bring together applied researchers and theorists, with the goal of understanding how each understands notions of generalization. There will be special emphasis on notions of generalization that do not have well-defined mathematical frameworks, but are frequent desiderata in applied research – for example, compositionality, systematicity, and task generalization. There will be invited speakers doing research in theory and natural language processing.
If you require special accommodation, please contact our access coordinator at simonsevents@berkeley.edu with as much advance notice as possible.
Uri Alon (Google DeepMind), Sanjeev Arora (Princeton University), Amanda Bertsch (Carnegie Mellon University), Jason Eisner (Johns Hopkins University), Surbhi Goel (University of Pennsylvania), Tatsunori Hashimoto (Stanford), Hamed Hassani (University of Pennsylvania), Nan Jiang (University of Illinois Urbana-Champaign), Zahra Kadkhodaie (New York University), Adam Kalai (OpenAI), Najoung Kim (Boston University), Frederic Koehler (University of Chicago), Sanmi Koyejo (Stanford University), Bingbin Liu (Carnegie Mellon University), Ankur Moitra (Massachusetts Institute of Technology), Vaishnavh Nagarajan (Google), Maxim Raginsky (University of Illinois at Urbana-Champaign), Max Simchowitz (Carnegie Mellon University), Leslie Valiant (Harvard University), Wei Xiong (UIUC), Diyi Yang (Stanford University)