Innovations in Theoretical Computer Science 2020 - Session 9

Explore cutting-edge research in theoretical computer science through this conference session from the Innovations in Theoretical Computer Science (ITCS) 2020 conference. Delve into six presentations covering diverse topics such as testing properties of multiple distributions, local access to huge random objects, learning monotone probability distributions, agreement expansion, spiking neural networks, and influence maximization. Chaired by Paul Beame, this session showcases research with strong conceptual messages, introducing new models, techniques, and applications in both traditional and interdisciplinary areas. Gain insights from speakers including Maryam Aliakbarpour, Sandeep Silwal, Ronitt Rubinfeld, and others as they present their groundbreaking work. Recorded on January 14, 2020, this closed-captioned video provides a comprehensive look at the latest advancements in theoretical computer science.

Innovations in Theoretical Computer Science 2020 Session 9