Session #1

Channel:
United States Simons Institute for the Theory of Computing
Subscribers:
68,600
Published on ● Video Link: https://www.youtube.com/watch?v=zNnfhG8ODN0


Duration: 48:21
408 views
3

Giulia Fanti (Carnegie Mellon University), Kate Donahue (Cornell), Sai Praneeth Karimireddy (UC Berkeley), Zachary Charles (Google)
https://simons.berkeley.edu/talks/giulia-fanti-carnegie-mellon-university-2023-07-19
Federated and Collaborative Learning

Giulia Fanti: Data Valuation and Trade Secret Privacy

Kate Donahue

Sai Praneeth Karimireddy: Uncertainty Quantification and Data Markets

Zachary Charles: Scaling Federated Learning to Foundation Models - Challenges & Opportunities



Other Videos By Simons Institute for the Theory of Computing


2023-07-26Testing Thresholds for High-dimensional Sparse Random Geometric Graphs
2023-07-25An Improved Bound for Regular Partitions of Hypergraph of Bounded VC_2 Dimension
2023-07-25Larger Corner-free Sets in High Dimensions
2023-07-25Top-Down Lower Bounds for Depth-Four Circuits
2023-07-25P-smallness of Increasing Families
2023-07-24Nearly all k-SAT Functions are Unate
2023-07-21Session #3
2023-07-20Survey on Optimization in FL
2023-07-20Session #2
2023-07-20Survey on Privacy/Security in FL
2023-07-20Session #1
2023-07-19Keynote
2023-07-19Another Round Of Breaking and Making Quantum Money: How to Not Build It From Lattices and More
2023-07-19Applications of Bit Commitments in a Quantum World
2023-07-19Pseudorandomness: From Quantum States to Binary Strings
2023-07-19Introduction to Quantum Cryptography Without One-Way Functions
2023-07-15Approaching the Quantum Singleton Bound with Approximate Error Correction
2023-07-14Improved Machine Learning Algorithm for Predicting Ground State Properties
2023-07-14Learning Beyond Stabilizer States
2023-07-14Quantum Commitments and Black Hole Radiation Decoding
2023-07-14Geometry, Entropy and Complexity in Quantum Gravity (Part II)


Tags:
Simons Institute
theoretical computer science
UC Berkeley
Computer Science
Theory of Computation
Theory of Computing
Federated and Collaborative Learning
Giulia Fanti
Kate Donahue
Sai Praneeth Karimireddy
Zachary Charles