Past Workshops and Seminars
November 11, 2022: Challenges in Data Economics Workshop
Erik Madsen Insider Imitation Video
Jon Kleinberg The Challenge of Understanding What Users Want: Inconsistent Preferences and Engagement Optimization Video
November 9, 2022: Theory Seminar – Tomasz Kociumaka
November 8, 2022: Theory Seminar – Sorrachai Yingchareonthawornchai
Deterministic Small Vertex Connectivity in Almost Linear Time Video
October 28, 2022: Elicitation and Evaluation Workshop
Mallesh Pai The Wisdom of the Crowd and Higher-Order Beliefs Video
Weijie Su A Truthful Owner-Assisted Scoring Mechanism Video Video
Rafael Frongillo Elicitation in Economics and Machine Learning Video
October 19, 2022: CS Seminar – Aadirupa Saha
Speaker: Aadirupa Saha, Toyota Technological Institute at Chicago
Title: Battling Bandits: Exploiting Preference Feedback towards Efficient Information Aggregation (Video)
October 14, 2022: Elicitation Mechanisms in Practice Workshop
Grant Schoenebeck, Peer prediction, Measurement Integrity, and the Pairing mechanism (Video)
Nihar Shah, Peer review, Incentives, and Open Problems (Video)
Kevin Leyton-Brown, Better Peer Review via AI (Video)
September 12, 2022: Theory-in-Practice Workshop
*watch the full morning event here
*watch the full after lunch event here
Speakers:
- Harsha Simhadri, Approximate Nearest Neighbor Search algorithms for web-scale search and recommendation (video)
- Stefan Muller, Static Prediction of Parallel Computation Graphs (video)
- Kunal Agrawal, Scheduling Algorithms for Real-time Systems (video)
- Jakub Łącki,
- Uzi Vishkin, Can parallel algorithms reverse the decline of general-purpose CPUs? (video)
September 6, 2022: CS Seminar- Meena Jagadeesan
Title: Machine Learning in Digital Marketplaces: Interactions between Learners, Consumers, and Producers
Speaker: Meena Jagadeesan, University of California, Berkeley
Panopto: https://www.ideal.northwestern.edu/special-quarters/fall-2022/workshops/panopto-9-6-22
September 7, 2022: CS Seminar Day Two- Meena Jagadeesan
Title: Learning Equilibria in Matching Markets from Bandit Feedback
Speaker: Meena Jagadeesan, University of California, Berkeley
Panopto: https://www.ideal.northwestern.edu/special-quarters/fall-2022/workshops/panopto-9-7-22
- Arnold Filtser, Locality-Sensitive Orderings
- Ainesh Bakshi, Robustly Learning a Mixture of k Arbitrary Gaussians
- Assaf Naor, Randomized clustering in high dimensions
- Erik Waingarten, The Johnson-Lindenstrauss Lemma for Clustering and Subspace Approximation
- Weiyun Ma, Almost 3-Approximate Correlation Clustering in Constant Rounds
May 13, 2022: Algorithms for Massive Data Sets
SPEAKERS:
- Sami Davies, Characterizing Good Predictions for Learning-augmented Algorithms with Instance-robustness (video)
- Sepideh Mahabadi, Non-Adaptive Adaptive Sampling in Turnstile Streams (video)
- Elizaveta Rebrova, Randomized projection methods for corrupted data (video)
- Jelani Nelson, Private Frequency Estimation via Projective Geometry (video)
- David Woodruff, Memory Bounds for the Experts Problem (video)
- Rachel Ward, Faster Johnson-Lindenstrauss embeddings via Kronecker products (video)
April 22, 2022: Clustering– Watch the full Friday event here
Speakers:
- Ola Svensson (EPFL) Watch the talk here
- Vincent Cohen-Addad (Google Research) Watch the talk here
- Sanjoy Dasgupta (UC San Diego) Watch the talk here
- Shi Li (University at Buffalo) Watch the talk here
- Lunjia Hu (Stanford) Watch the talk here
April 23, 2022: Clustering– Watch the full Saturday event here
Speakers:
- Liren Shan (Northwestern) Watch the talk here
- Vaggos Chatziafratis (UC Santa Cruz, Northwestern, MIT/Northeastern) Watch the talk here
- Jafar Jafarov (U Chicago) Watch the talk here
- Eden Chlamtáč (Ben-Gurion University, visiting TTIC) Watch the talk here
- Ali Vakilian (TTIC) Watch the talk here
November 16, 2021: Mini-workshop on New directions on Robustness in ML– watch the full event here
Speakers:
- Kamalika Chaudhuri (UC San Diego) Watch the talk here
- Pranjal Awasthi (Google Research) Watch the talk here
- Sebastien Bubeck (Microsoft Research) Watch the talk here
- Aleksander Madry (MIT) Watch the talk here
- Gautam Kamath (University of Waterloo) Watch the talk here
October 19, 2021: Mini-workshop on Statistical and Computational Aspects of Robustness in High-dimensional Estimation – watch the full event here
Speakers:
- Po-Ling Loh (Univ. of Cambridge) watch the talk here
- Ilias Diakonikolas (UW Madison) watch the talk here
- Ankur Moitra (MIT) watch the talk here
- Jacob Steinhardt (UC Berkeley) watch the talk here
September 21, 2021: Kickoff event for Fall Special Quarter on “Robustness in high dimensional statistics and machine learning” -Opening Remarks and Overview of the Fall 2021 Special Quarter program- watch the intro and overview here
Speakers:
- (University of Chicago) watch the talk here
May 28, 2021: CS+Law: Definitions for Algorithms
Speakers:
- Ran Canetti (Boston Univ.) Watch the talk here
- Jonathan Shafer (Univ. of Calif.-Berkeley) Watch the talk here
- Aloni Cohen (Boston Univ.) Watch the talk here
- Omer Reingold (Stanford Univ.) Watch the talk here
April 30, 2021: CS+Law: Evaluation and Accountability
Speakers:
- JJ Prescott (University of Michigan Law School) watch the talk here
- Maura Grossman (University of Waterloo, Computer Science) watch the talk here
- Cary Coglianese (University of Pennsylvania, Law School) watch the talk here
- Joan Feigenbaum (Yale University, Computer Science) watch the talk here
March 25, 2021: Technology and the Future of Courts: A Global Perspective – A Northwestern Law and Technology Initiative program
March 19, 2021: Quarterly Theory Workshop on “Algorithms and their Social Impact”
Speakers:
- Michael Kearns (University of Pennsylvania) watch the talk here
- Samira Samadi (MPI) watch the talk here
- Steven Wu (CMU) watch the talk here
- Suresh Venkatasubramanian (University of Utah) watch the talk here
- Rakesh Vohra (University of Pennsylvania) watch the talk here
- October 1st, 11:30 am Central: Seminar – Babak Hassibi (California Institute of Technology)
Watch the Recording of Babak Hassibi’s Talk
Title: “The Blind Men and the Elephant: The Mysteries of Deep Learning” - October 6th, 4:00 pm Central: Seminar – Julia Gaudio (MIT)
Watch the Recording of Julia Gaudio’s Talk
Title: “Regression Under Sparsity” - October 8th, 11:30 am Central: Seminar – Jason Lee (Princeton University)
Watch the Recording of Jason Lee’s Talk
Title: “Beyond Linearization in Deep Learning: Hierarchical Learning and the Benefit of Representation” - October 13th, 4:00 pm Central: Seminar – Daniel Hsu (Columbia University)
Watch the Recording of Daniel Hsu’s Talk
Title: “Contrastive learning, multi-view redundancy, and linear models” - October 15th, 11:30 am Central: Seminar – Quanquan Gu (UCLA)
Watch the Recording of Quanquan Gu’s Talk
Title: Learning Wide Neural Networks: Polylogarithmic Over-parameterization and A Mean Field Perspective - October 29th, 11:30 am Central: Seminar – Francis Bach (INRIA)
Watch the Recording of Francis Bach’s Talk
Title: “On the Convergence of Gradient Descent for Wide Two-Layer Neural Networks” - November 5th, 11:30 am Central: Seminar -Matus Telgarsky (University of Illinois, Urbana-Champaign)
Watch the Recording of Matus Telgarsky’s Talk
Title: The dual of the margin: improved analyses and rates of gradient descent’s implicit bias - November 10th, 4:00 pm Central: Seminar – Surbhi Goel (MSR NYC)
Watch the Recording of Surbhi Goel’s Talk
Title: Computational Complexity of Learning Neural Networks over Gaussian Marginals - November 12th, 11:30 am Central: Seminar – Emmanuel Abbe (EPFL)
Watch the Recording of Emmanuel Abbe’s Talk
Title: Learning monomials and separation between deep learning and SQ - November 19th, 11:30 am Central: Seminar – Rayadurgam Srikant (University of Illinois, Urbana-Champaign)
Watch the Recording of R. Srikant’s Talk
Title: The Role of Explicit Regularization in Overparameterized Neural Networks - December 1st, 11:30 am Central: Seminar – Edgar Dobriban (UPenn)
Watch the Recording of Edgar Dobriban’s Talk
Title: On the statistical foundations of adversarially robust learning - December 3rd, 11:30 am Central: Seminar – Andrea Montanari (Stanford University)
Watch the Recording of Andrea Montanari’s Talk
Title: The generalization error of random feature and neural tangent models
- May 5: Kickoff Workshop: Inference and Data Science on Networks
- May 13: Dean’s Lecture: Jon Kleinberg, Fairness and Bias in Algorithmic Decision Making
Public debates about classification by algorithms has created tension around what it means to be fair to different groups. Cornell University’s Jon Kleinberg will consider key fairness conditions at the heart of these debates, and discuss recent work on the interactions between these conditions. He will also explore how the complexity of a classification rule interacts with its fairness properties, showing how natural ways of approximating a classifier via a simpler rule can act in conflict with fairness goals. - May 14: Workshop: Estimation of Network Processes and Information Diffusion.
Many important dynamic processes are determined by an underlying network structure. Examples include the spread of epidemics, the dynamics of public opinions, the diffusion of information about social programs, and biological processes such as neural spike trains. Data about these processes is becoming increasingly available which has lead to a number of different research communities to tackle related questions independently. What is the source of a rumor? Will a given disease spread widely? Who is the key player? This workshop will cover some new tools being developed to address such questions. - June 29: Workshop: Computational vs Statistical Tradeoffs in Network Inference.