SimonsTV

Our videos can also be found on YouTube.
Extroverted Sublinear Algorithms
Monday, June 17 – Friday, June 21, 2024
Playlist: 24 videos
1.
New upper and lower bounds on approximate counting
Jelani Nelson (Simons Institute)
2.
Locally Private Histograms in All Privacy Regimes
Clément Canonne (University of Sydney)
3.
Shaving logs by weighing coins
Deeparnab Chakrabarty (Dartmouth College)
4.
Optimal Quantile Estimation for Streams
Mihir Singhal (UC Berkeley)
5.
O(log s)-Approximate Nearest Neighbor Search for the Earth Mover’s Distance
Rajesh Jayaram (Google Research NYC)
6.
Massively Parallel Algorithms for High-Dimensional Euclidean Minimum Spanning Tree
Peilin Zhong (Google)
7.
Efficiently Computing Similarities to Private Datasets
Sandeep Silwal (MIT)
8.
ML Efficiency for Large Models: From Data Efficiency to Faster Transformers
Vahab Mirrokni (Google Research, NYC)
9.
Sub-Linear Algorithms meets Large Language Models
Anshumali Shrivastava (Rice University)
10.
Randomized Least Squares Optimization and its Incredible Utility for Large-Scale Tensor Decomp...
Tamara Kolda (MathSci.ai)
11.
Long-context Attention in Near-Linear Time
David Woodruff (Carnegie Mellon University)
12.
Sublinear-Time Algorithms in Learning
Ronitt Rubinfeld (Massachusetts Institute of Technology)
13.
Large Scale Private Learning on Data Streams, and the BLTs
Abhradeep Guha Thakurta (Google DeepMind)
14.
Private video
15.
Sublinear Insights: A Faster (Classical) Algorithm for Edge Coloring
Sepehr Assadi (University of Waterloo and Rutgers University)
16.
Linear and sublinear algorithms for graphlet sampling
Marco Bressan (University of Milan)
17.
Sublinear algorithms in social networks via core-periphery decomposition
Omri Ben-Eliezer (Simons Institute)
18.
Sublinear time algorithms for better than 1/2 approximation algorithms for max-cut on expanders
Akash Kumar (IIT Bombay)
19.
Streaming Algorithms for Connectivity Augmentation
Ali Vakilian (Toyota Technological Institute at Chicago)
20.
Talk By Ilya Mironov (Google Brain)
Ilya Mironov (Google Brain)
21.
Applications of Sub-linear Algorithms on Other Fields
Vladimir Braverman (Rice University)
22.
Hypothesis selection with computational constraints
Maryam Aliakbarpour (Rice University)
23.
Lightning Talks
24.
A Bi-metric Framework for Fast Similarity Search
Piotr Indyk (Massachusetts Institute of Technology)
Logic and Algorithms in Database Theory and AI Boot Camp
Playlist: 20 videos
1.
Query Optimization and Evaluation 1: Output Size Bounds and Information Theory
Hung Ngo (RelationalAI)
2.
Query Optimization and Evaluation 2: Worst-Case Optimal Join Algorithms
Hung Ngo (RelationalAI)
3.
Query Optimization and Evaluation 3: Variable Elimination and Tensor Decomposition
Hung Ngo (RelationalAI)
4.
Query Optimization and Evaluation 4: Instance Optimality
Mahmoud Abo Khamis (RelationalAI)
5.
Logic and Probabilistic Circuits 1
Guy Van den Broeck (UCLA)
6.
Logic and Probabilistic Circuits 2
YooJung Choi (ASU)
7.
Logic and Probabilistic Circuits 3
YooJung Choi (ASU)
8.
Logic and Probabilistic Circuits 4
Guy Van den Broeck (UCLA)
9.
Algebraic Structures in Logic and Query Evaluation 1
Val Tannen (University of Pennsylvania)
10.
Algebraic Structures in Logic and Query Evaluation 2
Val Tannen (University of Pennsylvania)
11.
Fine-Grained Complexity 1
Virginia Vassilevska Williams (MIT)
12.
Fine-Grained Complexity 2
Nicole Wein (University of Michigan)
13.
Algebraic Structures in Logic and Query Evaluation 3
Dan Suciu (University of Washington)
14.
Algebraic Structures in Logic and Query Evaluation 4
Dan Suciu (University of Washington)
15.
Fine-Grained Complexity 3
Virginia Vassilevska Williams (MIT)
16.
Fine-Grained Complexity 4
Yinzhan Xu (MIT)
17.
Incremental View Maintenance 1
Dan Olteanu (University of Zurich)
18.
Incremental View Maintenance 2
Dan Olteanu (University of Zurich)
19.
Sampling in Query Evaluation 1
Marcelo Arenas (Pontificia Universidad Católica de Chile and RelationalAI)
20.
Sampling in Query Evaluation 2
Marcelo Arenas (Pontificia Universidad Católica de Chile and RelationalAI)
Continuous Algorithms: Sampling and Optimization in High Dimension
May. 2022
Santosh Vempala (Georgia Tech)
Simons Institute 10th Anniversary Symposium
Richard M. Karp Distinguished Lectures
Playlist: 40 videos
1.
Speculations on Test-Time Scaling | Richard M. Karp Distinguished Lecture
Sasha Rush (Cornell University)
2.
Lessons from Texas, COVID-19, and the 737 Max: Efficiency vs. Resilience | Richard M. Karp...
Moshe Vardi (Rice University)
3.
New Directions in Property Testing | Richard M. Karp Distinguished Lecture
Rocco Servedio (Columbia University)
4.
A Few Options Go a Long Way: List Decoding and Applications | Richard M. Karp Distinguished Lecture
Venkatesan Guruswami (Simons Institute, UC Berkeley)
5.
Locality in Codes and Computation | Richard M. Karp Distinguished Lecture
Noga Ron-Zewi (University of Haifa)
6.
Quantum Constraint Satisfaction | Richard M. Karp Distinguished Lecture
Sandy Irani (UC Irvine)
7.
The Complexity of Fermions in Quantum Information and Beyond | Richard M. Karp Distinguished Lecture
James Whitfield (Dartmouth)
8.
Private video
9.
Streaming (Synchronous), Recursion, and Incremental Computation
Val Tannen (University of Pennsylvania)
10.
The Power of Graph Learning | Richard M. Karp Distinguished Lecture
Floris Geerts (University of Antwerp)
11.
Dynamic Graph Algorithms: What We Know and What We Don’t | Richard M. Karp Distinguished Lecture
Monika Henzinger (Institute of Science and Technology Austria (ISTA))
12.
Introduction to Data Structures and Optimization for Fast Algorithms
Aaron Sidford (Stanford University)
13.
Structure of Communication | Richard M. Karp Distinguished Lecture
Shachar Lovett (UC San Diego)
14.
Erdős and Shannon: A Story of Probability, Communication, and Combinatorics
Jacob Fox (Stanford University)
15.
Gödel and the Vicious Circle: On the (In)Feasibility of Lower Bounds
Rahul Santhanam (University of Oxford)
16.
How Complex Is Complexity? Or What’s a ‘Meta’ for?
Eric Allender (Rutgers University)
17.
Graphons and Graphexes as Models of Large Sparse Networks
Jennifer Chayes (UC Berkeley)
18.
Pandora’s Box: Learning to Leverage Costly Information
Shuchi Chawla (University of Texas at Austin)
19.
Birds of a Feather Flock Together: How Homophily Leads to Segregation, Inequality, and...
Nicole Immorlica (Microsoft Research)
20.
Equilibrium Computation and Machine Learning
Constantinos Daskalakis (MIT)
21.
Causality and Autoencoders in Light of Drug Repurposing for COVID-19
Caroline Uhler (MIT)
22.
Secure Multiparty Computation
Yuval Ishai (Technion Israel Institute of Technology)
23.
Algorithmic Opportunities in Matching Markets
Vijay Vazirani (UC Irvine)
24.
Reductionism in Reinforcement Learning
Dale Schuurmans (Google Brain & University of Alberta)
25.
Is Your Distribution In Shape?
Ronitt Rubinfeld (MIT)
26.
Richard M. Karp Distinguished Lecture – Safe Learning in Robotics
Claire Tomlin (UC Berkeley)
27.
Insights on Gradient-Based Algorithms in High-Dimensional Learning
Lenka Zdeborová (CEA Saclay)
28.
Finding Large Cliques in Random and Semi-Random Graphs
Uriel Feige (Weizmann Institute of Science)
29.
Mathematical Imaging: From Geometric PDEs and Variational Modeling to Deep Learning for Images
Carola-Bibiane Schönlieb (University of Cambridge)
30.
Computational Barriers in Statistical Estimation and Learning
Andrea Montanari (Stanford)
31.
On Some Optimization Problems Involving a Large Number of Matrices
Wilfrid Gangbo (UCLA)
32.
Richard M. Karp Distinguished Lecture — How Difficult is it to Certify that a Random SAT Formula is
Toniann Pitassi (University of Toronto)
33.
Back to the Future: A Fresh Look at Linear Temporal Logic
Javier Esparza (Technical University of Munich)
34.
Trustworthy and Distributed Automated Reasoning
Marijn Heule (Carnegie Mellon University)
35.
Richard M. Karp Distinguished Lecture — Automated Formal Program Repair
Orna Grumberg (Technion - Israel Institute of Technology)
36.
Average-Case Complexity through the Lens of Interactive Arguments
Rafael Pass (Cornell University)
37.
Byzantine Fault Tolerance Meets Flexibility
Dahlia Malkhi (Calibra)
38.
A Tale of Turing Machines, Quantum-Entangled Particles, and Operator Algebras
Henry Yuen (University of Toronto)
39.
Lattices, Post-Quantum Security and Homomorphic Encryption
Daniele Micciancio (UC San Diego)
40.
Lattices ∩ Quantum
Zvika Brakerski (Weizmann Institute of Science)
ITCS 2022 (live sessions)
13th Innovations in Theoretical Computer Science Conference (ITCS 2022)
Playlist: 26 videos
1.
ITCS 2022 Session 1
Chair: Igor Oliveira
2.
ITCS 2022 Session 2
Chair: Lijie Chen
3.
ITCS 2022 Session 3
Chair: Mahsa Derakhshan
4.
ITCS 2022 Session 4
Chair: Yang Cai
5.
ITCS 2022 Session 5
Chair: Ken Clarkson
6.
ITCS 2022 Session 6
Chair: Karthik C. S.
7.
ITCS 2022 Session 7
Chair: Frederic Magniez
8.
ITCS 2022 Graduating Bits
Chair: Gautam Kamath
9.
ITCS 2022 Session 8
Chair: Eylon Yogev
10.
ITCS 2022 Session 9
Chair: Rotem Oshman
11.
ITCS 2022 Session 10
Chair: Ariel Schvartzman
12.
ITCS 2022 Session 11
Chair: Aditya Bhaskara
13.
ITCS 2022 Session 12
Chair: Omri Ben-Eliezer
14.
ITCS 2022 Graduating Bits
Chair: Gautam Kamath
15.
ITCS 2022 Session 13
Chair: Josh Alman
16.
ITCS 2022 Session 14
Chair: Eylon Yogev
17.
ITCS 2022 Session 15
Chair: Rafael Oliveira
18.
ITCS 2022 Session 16
Chair: Raghuvansh R. Saxena
19.
ITCS 2022 Session 17
Chair: Nicole Wein
20.
ITCS 2022 Session 18
Chair: Xue Chen
21.
ITCS 2022 Session 19
Chair: Maryam Aliakbarpour
22.
ITCS 2022 Session 21
Chair: Antonina Kolokolova
23.
ITCS 2022 Session 22
Chair: Makrand Sinha
24.
ITCS 2022 Session 23
Chair: Yuval Filmus
25.
ITCS 2022 Session 24
Chair: Noga Ron-Zewi
26.
ITCS 2022 Session 20
Chair: Alex Grilo
Deep Robust Reinforcement Learning and Regularization
Oct. 2020
Shie Mannor (Technion)
https://simons.berkeley.edu/talks/tbd-226
Deep Reinforcement Learning
WIT: Women in Theory (of Computer Science) — I Will Survive!
May. 2020
The Women of Theory of Computer Science rock to our version of I Will Survive!
WIT: https://womenintheory.wordpress.com/


I Will Survive
Lyrics: Avi Wigderson (IAS)

At first I was afraid, I was petrified
I worried I could never fit this proof on just one slide
But then I spent so many nights thinking why it is so long
And I grew strong
And learned exactly what went wrong

A problem wor-thy, of attack
Just proves its worth by vigorously fighting back
I should have used error correction, should have sampled yet again
I should have stayed the course and found there is so much that I can gain

So do come back, problems galore
I am much more ready to attack you than I was before
I’ll fight you guiltless when at work, forget you guiltless when at home
And if you’re fun then in the pastures of the TCS we’ll roam

So I’ll survive, and I will thrive,
By Nash’s equilibrium, there must be balance to my life
I’ve got all my life to live,
And I’ve got all my Math to give
So I’ll survive,
and I will thrive, hey, hey

It took all the strength I had, I was nearly spent,
Trying hard to mend, the errors, in my argument
I put each pigeon in its hole, consulted every oracle
My upper bound
Turned up below my lower bound

Then I came up, with something new
I thought outside the blackbox, found what others never knew
That polynomials with a small degree have small number of roots
That few cryptogra-phic assumptions no one’s likely to dispute

So do come back, problems galore
I am much more ready to attack you than I was before
As I have wit and I have WIT and having both is pretty neat
Indeed a convex combination that is very hard to beat

So I’ll survive, and I will thrive,
Because (in theory, at least) this is a perfect life
You pick the problems that you love
To fit your brain just like a glove
So I’ll survive,
and I will thrive, hey, hey

Singers:
Dahlia Malkhi (Calibra, Facebook)
Elette Boyle (IDC, Israel)
Irit Dveer Dinur (Weizmann Institute, Israel)
Julia Chuzhoy (Toyota Technological Institute at Chicago, USA)
Katrina Ligett (Hebrew University, Israel)
Keren Censor-Hillel (Technion, Israel)
Lisa Zhang (Bell-Labs, USA)
Mary Wooters (Stanford University, USA)
Michal Feldman (Tel-Aviv University, Israel)
Nicole Immorlica (Microsoft Research, New England, USA)
Orna Kupferman (Hebrew University, Israel)
Rebecca Wright (Barnard College, USA)
Ronitt Rubinfeld (MIT, USA)
Shafi Goldwasser (Simons Institute at UC Berkeley, USA)
Shubhangi Saraf (Rutgers University, USA)
Shuchi Chawla (University of Wisconsin, Madison, USA)
Sofya Raskhodnikova (Boston University, USA)
Tal Malkin (Columbia University, USA)
Tal Rabin (Algorand Foundation, USA)
Yael Tauman Kalai (Microsoft Research, New England, USA)
Interpretability - now what?
Jul. 2019
Been Kim (Google Brain)
https://simons.berkeley.edu/talks/tbd-72
Frontiers of Deep Learning
The Quantum Wave in Computing
May. 2019
Urmila Mahadev, UC Berkeley
Fifth Annual Industry Day
Lower Bounds in Computational Complexity Boot Camp
Playlist: 20 videos
1.
Circuit Lower Bounds from Algorithm Design: An Overview I (Partial)
Ryan Williams, MIT
2.
Circuit Lower Bounds from Algorithm Design: An Overview II
Ryan Williams, MIT
3.
Restriction-based Methods I
Ben Rossman, University of Toronto
4.
Restriction-based Methods II
Ben Rossman, University of Toronto
5.
Lower Bounds Techniques in Proof Complexity I
Pavel Hrubes, Academy of Sciences of the Czech Republic
6.
Lower Bounds Techniques in Proof Complexity II
Pavel Hrubes, Academy of Sciences of the Czech Republic
7.
Derandomization from Circuit Lower Bounds I
Russell Impagliazzo, UC San Diego
8.
Derandomization from Circuit Lower Bounds II
Russell Impagliazzo, UC San Diego
9.
Geometric Complexity Theory I: Complexity Lower Bounds...
Christian Ikenmeyer, Max Planck Institute for Informatics
10.
Geometric Complexity Theory II: Complexity Lower Bounds...
Christian Ikenmeyer, Max Planck Institute for Informatics
11.
Lower Bounds in Arithmetic Circuit Complexity I
Srikanth Srinivasan, Indian Institute of Technology Bombay
12.
Lower Bounds in Arithmetic Circuit Complexity II
Srikanth Srinivasan, Indian Institute of Technology Bombay
13.
Communication Complexity I
Anup Rao, University of Washington
14.
Communication Complexity II
Anup Rao, University of Washington
15.
Lower Bounds for Dynamic Data Structures I
Kasper Green Larsen, Aarhus University
16.
Lower Bounds for Dynamic Data Structures II
Kasper Green Larsen, Aarhus University
17.
Time-Space Lower Bounds for Learning I
Avishay Tal, Stanford University
18.
Time-Space Lower Bounds for Learning II
Avishay Tal, Stanford University
19.
Impossibility Results for Distributed Computing I
Faith Ellen, University of Toronto
20.
Impossibility Results for Distributed Computing II
Faith Ellen, University of Toronto
Analog Quantum Simulations: What We Have, What We Would like to Have, and the...
Jun. 2018
Jens Eisert, Freie Universität Berlin
https://simons.berkeley.edu/talks/jens-eisert-06-11-18
Challenges in Quantum Computation
The Deep Learning Revolution: What Does It Tell Us About Our Understanding of Intelligence?
Apr. 2018
Naftali Tishby (Hebrew University of Jerusalem)
Simons Institute Open Lecture Series, Spring 2018
https://simons.berkeley.edu/events/openlectures2018-spring-3
Targeted Discovery in Brain Data
This workshop will focus on the problem of inferring structure from neuroscience data, including the following specific themes:
Playlist: 13 videos
1.
Three Principles of Data Science: Predictability, Stability, and Computability
Bin Yu, UC Berkeley
2.
Private video
3.
Decoding and Modeling the Brain’s Navigational Circuits
Ila Fiete, University of Texas at Austin
4.
Cortical Travelling Waves: Mechanisms and Computational Principles
Terry Sejnowski, Salk Institute
5.
Computational Geometry of Cortical Networks: Manifold-Embedding Analysis of Multi-Site Recordings...
Clay Reid, Allen Institute for Brain Science
6.
Private video
7.
Automated Reconstruction of Synaptic-Resolution Neural Wiring Diagrams Using...
Viren Jain, Google
8.
Private video
9.
The Information Bottleneck Theory of Deep Neural Networks...
Naftali Tishby, Hebrew University of Jerusalem
10.
Cortical Areas Interact through a Communication Subspace
Christian Machens, Champalimaud Research
11.
Similarity Alignment: A Missing Link Between Structure, Function and Algorithms
Mitya Chklovskii, Simons Foundation
12.
Tracing, Intercepting and Modeling Communication in the Brain
Fritz Sommer, UC Berkeley
13.
Inferring Single-Trial Neural Population Dynamics Using Sequential Auto-Encoders
David Sussillo, Google
Basal Ganglia Architecture for Reinforcement Learning
Feb. 2018
Josh Berke, UCSF
https://simons.berkeley.edu/talks/josh-berke-2-13-18
Representation, Coding and Computation in Neural Circuits
Hierarchies, Extended Formulations and Matrix-Analytic Techniques
An important development in the area of convex relaxations has been the introduction of systematic ways of strengthening them by lift-and-project techniques. This leads to several hierarchies of LP/SDP relaxations: Lovasz-Schrijver, Sherali-Adams and Sum of Squares (also known as the Lasserre hierarchy). The benefits and limitations of these hierarchies have been studied extensively over the last decade. Recently, strong negative results have been obtained, not only for specific hierarchies but even for the more general notion of extended formulations. In this workshop we investigate the power and limitations of LP/SDP hierarchies as well as general extended formulations, and their ties to convex algebraic geometry. We also explore tools and concepts from matrix analysis with strong connections to SDP formulations: matrix concentration, matrix multiplicative weight updates, and various notions of matrix rank. Finally, the workshop will cover related areas where these kinds of techniques are employed: sparsification, discrepancy and hyperbolic/real stable polynomials.
Playlist: 24 videos
1.
Constructing Extended Formulations
Volker Kaibel, Otto-von-Guericke-Universität Magdeburg
2.
Small (Explicit) Extended Formulation for Knapsack Cover Inequalities from Monotone Circuits
Sam Fiorini, Université Libre de Bruxelles
3.
Computing the Nucleolus of Weighted Cooperative Matching Games in Polynomial Time
Kanstantin Pashkovich, University of Waterloo
4.
A Lower Bound on the Positive Semidefinite Rank of Convex Bodies
Hamza Fawzi, University of Cambridge
5.
Bounds for Matrix Factorization Ranks via Semidefinite Programming and...
Monique Laurent, CWI Amsterdam
6.
Using Symmetry in Semidefinite Programming
Annie Raymond, University of Washington
7.
Sparse Polynomial Interpolation: Compressed Sensing, Super-resolution, or Prony?
Jean-Bernard Lasserre, CNRS
8.
Pseudocalibration and SoS Lower Bounds
Sam Hopkins, Cornell University and Aaron Potechin, Institute for Advanced Study
9.
Weak Decoupling, Polynomial Folds, and Approximate Optimization over the Sphere
Vijay Bhattiprolu, Carnegie Mellon University
10.
Spectral Aspects of Symmetric Matrix Signings
Alexandra Kolla, University of Illinois at Urbana-Champaign
11.
From Weak to Strong LP Gaps for all CSPs
Madhur Tulsiani, Toyota Technological Institute at Chicago
12.
LP, SOCP, and Optimization-Free Approaches to Polynomial Optimization
Amir Ali Ahmadi, Princeton University
13.
Matrix Completion and Sums of Squares
Greg Blekherman, Georgia Institute of Technology
14.
SOS and the Dreaded Bit-complexity
Ryan O'Donnell, Carnegie Mellon University
15.
Maximizing Sub-determinants and Connections to Permanents and Inequalities on Stable Polynomials
Mohit Singh, Georgia Institute of Technology
16.
Spectrahedra and Directional Derivatives of Determinants
James Saunderson, Monash University
17.
Counting and Optimization Using Stable Polynomials
Nima Anari, Stanford University
18.
Independent Set Polytopes: Query vs. Communication Perspective
Mika Göös, University of Toronto
19.
Approximating Rectangles by Juntas and Weakly-Exponential Lower Bounds for LP Relaxations of CSPs
Raghu Meka, UCLA
20.
From Proofs to Algorithms for Machine Learning Problems
David Steurer, Cornell University
21.
Nonnegative Polynomials, Nonconvex Polynomial Optimization, and Applications to Learning
Georgina Hall, Princeton University
22.
Fast Spectral Algorithms from Sum-of-Squares Analyses
Tselil Schramm, UC Berkeley
23.
Computing the Independence Polynomial in Shearer's Region for the LLL
Nick Harvey, University of British Columbia
24.
Quantum Entanglement, Sum of Squares, and the Log Rank Conjecture
Pravesh Kothari, Princeton University
Probabilistic Programming for Augmented Intelligence
Oct. 2016
Vikash Mansinghka, MIT
https://simons.berkeley.edu/talks/vikash-mansinghka-10-06-2016
Uncertainty in Computation
Network Biology
Apr. 11 – Apr. 15, 2016
Playlist: 28 videos
1.
Using Molecular Networks to Seed Predictive Hierarchies of Cell Systems
Trey Ideker, UC San Diego
2.
Uncertainty in Biological Networks; Challenges and Opportunities
Tamer Kahveci, University of Florida
3.
Diffusion-Based Metrics for Biological Network Analysis
Lenore Cowen, Tufts University
4.
Sampling the Low End of Affinity
Marcus Noyes, New York University
5.
Systematic Functional Annotation of the 2016 Yeast Genetic Interaction Network
Anastasia Baryshnikova, Princeton University
6.
Pathways, Centrality, and Regulation in Developmental Disorders
Donna Slonim, Tufts University
7.
On Beyond Genome: Opportunities and Challenges Using the Other Omics for Precision Medicine
Ernest Fraenkel, Massachusetts Institute of Technology
8.
Algorithms for Combinatorial Problems Arising in the Analysis of Cancer Mutation Networks
Fabio Vandin, University of Padova
9.
Network Analysis of Cancer Mutations
Ben Raphael, Brown University
10.
Fathoming Cancer by Interrogating Integrated Interactomes
Igor Jurisica, Princess Margaret Cancer Centre
11.
Network Data Integration Enables Precision Medicine
Natasa Przulj, University College London
12.
Transcriptional Enhancers - Looking out for the Genes and Each Other
Sridhar Hannenhalli, University of Maryland
13.
Dynamics of 3D Enhancer-Gene Associations Across Diverse Human Cell Types and Tissues
Anshul Kundaje, Stanford University
14.
Profiling Cell/Tissue Specific Gene Regulatory Networks
Louxin Zhang, National University of Singapore
15.
Variation of Regulatory Networks Across Organisms
Mona Singh, Princeton University
16.
Spatial Gene Expression Patterns in Drosophila
Bin Yu, UC Berkeley
17.
Network Perspective on Expression Changes and Expression Noise in D. melanogaster Chromosomal Deleti
Teresa Przytycka, National Institutes of Health
18.
Cross-Species Interactome Mapping Reveals Network Evolution Principles from Yeasts to Human
Haiyuan Yu, Cornell University
19.
Moving Beyond Local Patterns: New Ways to Reason about Biological Network Comparisons
Ben Hescott, Tufts University
20.
Data Driven "Pathway" Analysis with ADAGE
Casey Greene, University of Pennsylvania
21.
Synthesis, Simplification and Analysis of Biological Networks Using Higher Order Topological Connect
Bhaskar DasGupta, University of Illinois at Chicago
22.
Network Propagation as a Tool for Deciphering Disease Mechanisms
Roded Sharan, Tel-Aviv University
23.
Dynamic and Integrative Biological Network Research of Aging
Tijana Milenkovic, University of Notre Dame
24.
Efficiently Enumerating All Connected Induced Subgraphs of a Large Molecular Network
Mehmet Koyuturk, Case Western Reserve University
25.
Identifying Disease Mechanisms Using Gene Networks as Priors
Anna Goldberg, University of Toronto
26.
Simple Models and Exact Algorithms for Computing Network Modules
Gunnar Klau, CWI, Amsterdam
27.
Local Similarity Analysis (LSA) of Time Series Data and Applications to Metagenomics
Fengzhu Sun, University of Southern California
28.
Module Discovery in 3-way Data
Ron Shamir, Tel-Aviv University
From the Inside: Economics and Computation
Dec. 2015
Richard Karp sat down with Tim Roughgarden to discuss the Fall 2015 program on Economics and Computation.

https://simons.berkeley.edu/programs/economics2015
Algorithmic Game Theory and Practice
Nov. 16 – Nov. 20, 2015
Playlist: 23 videos
1.
Kidney Exchange: Algorithms and Incentives
Alvin Roth, Stanford University
2.
Designing Online Advertising Markets
Susan Athey, Stanford University
3.
Outsourcing Tasks Online: Matching Supply and Demand on Peer-to-Peer Internet
Chiara Farronato, Harvard University
4.
Business Model Analysis
Kamal Jain, Faira.com
5.
The Limits of Reputation in Platform Markets
Steve Tadelis, UC Berkeley
6.
Adverse Selection and Auction Design for Internet Display Advertising
Paul Milgrom, Stanford University
7.
Machine Learning in an Exchange Environment
R. Preston McAfee, Microsoft
8.
Online Advertisements and Online Algorithms
Nikhil Devanur, Microsoft Research
9.
On How Machine Learning and Auction Theory Power Facebook Advertising
Eric Sodomka, Facebook
10.
On-Line Systems with Long-Range Goals
Jon Kleinberg, Cornell University
11.
Decision Making at Scale: Platforms and Problems
Ashish Goel, Stanford University
12.
Strong Truthfulness in Multi-signal Peer Prediction with Overlapping Tasks
David Parkes, Harvard University
13.
The State of Techniques for Solving Large Imperfect-Information Games
Tuomas Sandholm, Carnegie Mellon University
14.
Security Games: Key Algorithmic Principles, Deployed Applications and Research Challenges(*)
Milind Tambe, University of Southern California
15.
Robust Inference for Games via Theoretical Guarantees
Denis Nekipelov, University of Virginia
16.
An Evolutionary Model of Economic Behavior, Bounded Rationality, and Intelligence
Andrew Lo, Massachusetts Institute of Technology
17.
The Design of Financial Exchanges: Some Open Questions at the Intersection of Econ and CS
Eric Budish, University of Chicago
18.
Algorithmic Trading and Machine Learning
Michael Kearns, University of Pennsylvania
19.
Incentive Auctions and Spectrum Repacking
Kevin Leyton-Brown, University of British Columbia
20.
Informational Substitutes and Complements for Prediction
Yiling Chen, Harvard University
21.
AGT and Machine Learning
Christos Papadimitriou, UC Berkeley
22.
Bitcoin's Incentive Structure
Aviv Zohar, Hebrew University of Jerusalem
23.
Dynamic Pricing in Ride-Sharing Platforms
Ramesh Johari, Stanford University
Securing Computation
Jun. 8 – Jun. 12, 2015
Playlist: 32 videos
1.
Obfuscation: Past, Present, and Possible Futures
Amit Sahai, UCLA
2.
New Developments in Multilinear Maps: Zeroizing Attacks, Defenses, and Post-Zeroizing Obfuscation
Eric Miles, UCLA
3.
Indistinguishability Obfuscation for Turing Machines with Unbounded Memory
Brent Waters, University of Texas, Austin
4.
Obfuscation with Constant Multiplicative Size Overhead
Prabhanjan Ananth, UCLA
5.
Cryptocurrencies and Smart Contracts
Elaine Shi, University of Maryland
6.
Sequential Composition of Rational Proofs
Rosario Gennaro, City University of New York
7.
Rethinking Secure Computation - A Greedy Approach
Muthuramakrishnan Venkitasubramaniam, University of Rochester
8.
A Brief History of Practical Garbled Circuit Optimizations
Mike Rosulek, Oregon State University
9.
Fast Garbling of Circuits Under Standard Assumptions
Yehuda Lindell, Bar-Ilan University
10.
A Framework for Efficient Mixed-Protocol Secure Two-Party Computation
Thomas Schneider, Technische Universität Darmstadt
11.
Lower Bounds for Information-Theoretic MPC
Ivan Damgård, Aarhus University
12.
Capacity Inversion and MPC over Elastic Noisy Channels
Hemanta Maji, UCLA
13.
Upending Stock Market Structure Using Secure Computation
Charanjit Jutla, IBM T.J. Watson Research Center
14.
Practical Private DB Querying
Vlad Kolesnikov, Bell Labs
15.
A Wishlist for Verifiable Computation: An Applied CS Perspective
Mike Walfish, New York University
16.
SNARKs and their Practical Applications
Eran Tromer, Tel Aviv University
17.
How to use Bitcoin to Enhance Secure Computation
Ranjit Kumaresan, Massachusetts Institute of Technology
18.
Provably Secure Blockchain Protocols and Applications to Secure Computation
Aggelos Kiayias, University of Athens
19.
The Simplest Oblivious Transfer Protocol
Claudio Orlandi, Aarhus University
20.
The Whole is Greater than the Sum of its Parts: Linear Garbling and Applications
Valerio Pastro, Columbia University
21.
Contention in Cryptography: Obfuscation, Leakage, UCE and the AI-DHI Assumptions
Stefano Tessaro, UC Santa Barbara
22.
How to Construct Indistinguishability Obfuscation from Compact Functional Encryption
Abhishek Jain, Johns Hopkins University
23.
Public-Coin Differing-Inputs Obfuscation and its Applications
Omkant Pandey, UCLA
24.
Obfuscation of Probabilistic Circuits and Applications
Huijia Lin, UC Santa Barbara
25.
Two Round MPC via Multi-Key FHE
Daniel Wichs, Northeastern University
26.
Efficient Multiparty Protocols via Log-Depth Threshold Formulae
Ron Rothblum, Weizmann Institute
27.
Oblivious RAM for MPC
Stanislaw Jarecki, UC Irvine
28.
Provably Secure Virus Detection: Using the Uncertainty to End Computer Malware
Vassilis Zikas, ETH Zürich
29.
On the Cryptographic Hardness of Finding a Nash Equilibrium
Omer Paneth, Boston University
30.
How Fair is your Protocol? A Utility-Based Approach to Protocol Optimality
Bjoern Tackmann, UC San Diego
31.
Cryptographic Agents: Towards a Unified Theory of Computing on Encrypted Data
Manoj Prabhakaran, University of Illinois, Urbana‑Champaign
32.
New Advances in Secure RAM Computation
Sanjam Garg, UC Berkeley