Dates and Location:

June 14-15, 2022

6/14 @ the John Crerar Library (home of UChicago CS Department), 5730 S Ellis Ave, Chicago, IL 60637

6/15 @ the ​​Toyota Technological Institute at Chicago, 6045 S Kenwood Ave, Chicago, IL 60637

Hotels:

• The Study At Univ Of Chicago — right on campus, halfway between CS department and TTIC. For reserving at the military rate at The Study, guests can contact their reservations department directly at reservations.chicago@studyhotels.com or by calling 773-643-1600. The rate will be $216 for June.
• Sophy Hyde Park — off campus but very close; close to restaurants, bars, shops
• Hyatt Place — off campus but very close; close to restaurants, bars, shops. UChicago Friend and Family discount available; rate would be $178. To book online using the government rate at the Hyatt, guests simply select “Government” under ‘Special Rates’ to view/book this; for June that rate is $212.

Banquet:

Planned for Promontory Point, right on Lake Michigan.

Schedule:

Day 1, June 14th (@ John Crerar Library)

8:45 – 9:15 Coffee, gathering

9:15 – 9:30 Welcoming remarks (Becca, Rob, Lee, Erik)

9:30 – 10:00 Talk 1 on Data-Efficient ML (Jerry Zhu): Efficient Data Collection for Learning Requires Incentives

10:00 – 10:30 Talk 2 on Data-Efficient ML (“Interactive Learning for Mission Planning” by Scott Sievert)

10:30 – 10:45 Break

10:45 – 12:00 Day 1 Lightning talks

12:00 – 13:30 Lunch

13:30 – 14:00 Talk 3 on Operational Robustness (Karen)

14:00 – 14:30 Talk 4 on Operational Robustness (Ashley Prater-Bennette – video)

14:30 – 15:00 Break

15:00 – 17:00 Day 1 Poster session

18:00 – 21:00 Banquet

Day 1 Lightning Talks

• Yuxin Chen, UChicago, Teaching an Active Learner with  Contrastive Examples
• Rob Nowak, U-W Madison, Training Out-of-Distribution Detectors in the Wild
• Rebecca Willett, UChicago, Auto-differentiable Ensemble Kalman Filters
• Andre Beckus, AFRL,  A methodology for flattening the command and control problem space
• Yinglun Zhu, UW-Madison, Towards Statistical and Computational Efficiencies in Active Learning 
• Greg Canal, UW-Madison, One for All: Simultaneous Metric and Preference Learning over Multiple Users
• Simon Khan, AFRL, User Authentication by Fusion of Mouse Dynamics and Widget Interactions: Two Experiments with PayPal and Facebook
• Jerry Zhu, UW-Madison,  Creative Bandit: Generating More and Better Training Data
• Jake Soloff, UChicago, TBD
• Erik Blasch, AFOSR, Motivation towards Certifiable AI
• Zhenmei Shi, UW-Madison, A Theoretical Analysis on Feature Learning in Neural Networks: Emergence from Inputs and Advantage over Fixed Features; Towards Evaluating the Robustness of Neural Networks Learned by Transduction

Day 1 Posters

• Daniel Park, AFRL, Towards Cost-Constrained Adversarial Examples 
• Claire Hardy, AFRL, Common and Uncommon Feature Extractor Robustness Against Novel Input
• Walter Bennette, AFRL, Hierarchical Open-Set Recognition
• Sean Sisti, AFRL, TBD
• Amy Wong, AFRL, KnowML
• Young Wu, UW-Madison, MARL Poisoning
• Elena Orlova, UChicago, ML for Subseasonal forecasting
• Nathan McDonald, AFRL, Online Learning with Hyperdimensional …
• Ruoxi Jiang, UChicago, Embed and Emulate: Learning to estimate parameters of dynamical systems with uncertainty quantification
• Jayaram Raghuram, UW-Madison, Stratified Adversarial Robustness with Rejection
• Cody Kearse, AFRL, Modularized Class Specific Neural Network Configurations for Precision Training
• Alex Hildenbrandt & Ashley Diehl, AFRL, Robust and Secure Machine Learning
• Jeremy McMahan, UW-Madison, Offline Data Poisoning in MARL
• Ankita Pasad, TTIC, Layer-Wise Analysis Of Self-Supervised Speech Models
• Danica Fliss, UW-Madison, Plug-and-Play Methods for Satellite Image Restoration

Day 2, June 15th (@ TTIC):

9:00 – 9:30 Coffee, gathering

9:30 – 10:00 Talk 5 on Adversarial Robustness (Yingyu)

10:00 – 10:30 Talk 6 on Adversarial Robustness (Ryan Luley)

10:30 – 10:45 Break

10:45 – 12:00 Day 2 Lightning talks

12:00 – 13:30 Lunch + Day 2 Poster session

13:30 – 14:00 Talk 7 on Computationally Efficient ML (Lipasti): PrGEMM: Hardware Acceleration for Sparse Matrix Multiply

14:00 – 14:30 Talk 8 on Computationally Efficient ML (Bai): Toward Intelligence in Communication Networks.

14:30 – 15:15 Panel

15:15+ Unstructured research meetings

Day 2 Lightning Talks

• Jeremy McMahan, UW-Madison, Offline Data Poisoning in MARL
• Benjamin Robinson, AFRL, High-Dimensional Principal Components and Signal Detection
• Jy-yong Sohn, UW-Madison, GenLabel: Mixup Relabeling using Generative Models
• David Uminsky, UChicago, TBD
• Shageenth Sandrakumar, AFRL, TBD
• Kangwook Lee, UW-Madison, TBD
• Michael Maire, UChicago, Faster Training by Growing Deep Networks
• Alex Alaniz, AFRL, Weapons engagement OPtimizeR (WOPR)
• Cong Ma, UChicago, Scaling and Scalability: Provable Nonconvex Low-Rank Tensor Estimation from Incomplete Measurements
• Shubham Kumar Bharti, UW-Madison, Towards provable defenses against trojan attacks in RL

Day 2 Posters

• Simon Khan, AFRL, User Authentication by Fusion of Mouse Dynamics and Widget Interactions: Two Experiments with PayPal and Facebook
• Zhenmei Shi, UW-Madison, A Theoretical Analysis on Feature Learning in Neural Networks: Emergence from Inputs and Advantage over Fixed Features; Towards Evaluating the Robustness of Neural Networks Learned by Transduction
• Clare Thiem, AFRL, NeuroPipe: A combined Development Pipeline for Novel Neuromorphic Hardware
• Andre Beckus, AFRL, Methodology for Flattening the Command and Control Problem Space
• Kartik Sreenivasan, UW-Madison, Rare Gems: Finding Lottery Tickets at Initialization
• Kang Jun Bai, AFRL, Toward Intelligence in Communication Networks
• Cong Ma, UChicago, Scaling and Scalability: Provable Nonconvex Low-Rank Tensor Estimation from Incomplete Measurements
• Shubham Kumar Bharti, UW-Madison, Towards provable defenses against trojan attacks in RL
• Chien-Fu Chen, UW-Madison, Poster: PrGEMM: A Parallel Reduction SpGEMM Accelerator
• Xiaodan Du, TTIC, Learning a Natural Language Interface for Pretrained Image Generators
• Jiahao Li, TTIC, Adapting CLIP For Phrase Localization Without Further Training
• David Yunis, TTIC, Singular dynamics and linear mode connectivity in neural networks
• Junyi Wei, UW Madison, An efficient self-supervised training method for Detr