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America/Los_Angeles
 
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SUN 10 DEC
7 a.m.
(ends 4:00 PM)
noon
Expo Demonstration:
(duration 1.5 hr)
Expo Talk Panel:
(ends 12:50 PM)
Expo Talk Panel:
(ends 12:50 PM)
Expo Workshop:
(ends 2:00 PM)
Expo Workshop:
(ends 2:00 PM)
Expo Workshop:
(ends 2:00 PM)
Expo Workshop:
(ends 2:00 PM)
1 p.m.
Break:
(ends 1:30 PM)
2:30 p.m.
Break:
(ends 3:00 PM)

MON 11 DEC
5:30 a.m.
(ends 4:00 PM)
6 a.m.
Workshop:
(ends 1:30 PM)
6:15 a.m.
Workshop:
(ends 1:30 PM)
Workshop:
(ends 1:30 PM)
Workshop:
(ends 1:30 PM)
6:30 a.m.
Workshop:
(ends 1:30 PM)
Workshop:
(ends 1:30 PM)
7 a.m.
Workshop:
(ends 1:15 PM)
7:15 a.m.
Break:
(ends 8:05 AM)
7:30 a.m.
Workshop:
(ends 1:30 PM)
9 a.m.
Workshop:
(ends 12:00 PM)
10 a.m.
Education Outreach:
(ends 11:40 AM)
10:15 a.m.
Lunch:
(ends 11:45 AM)
1:30 p.m.
Affinity Poster Session:
(ends 2:30 PM)
2 p.m.
Break:
(ends 2:45 PM)
3 p.m.
Opening Remarks:
(ends 3:25 PM)
3:25 p.m.
Invited Talk:
Björn Ommer
(ends 4:15 PM)
4:15 p.m.
Reception:
(ends 6:30 PM)
4:30 p.m.
Chairs: Jean Oh · Isabelle Guyon
s 4:30-6:00
[4:30] Voice Scroll
[4:30] The WHOOPS! Gallery: An Intersection of AI, Creativity, and the Unusual
[4:30] Kiss/Crash
[4:30] Emergent Rhythm — Real-time AI Generative DJ Set
[4:30] Fusion: Landscape and Beyond
[4:30] Entanglement
(ends 6:00 PM)

TUE 12 DEC
5:30 a.m.
(ends 4:00 PM)
6:30 a.m.
Invited Talk:
Lora Aroyo
(ends 7:20 AM)
7:15 a.m.
Break:
(ends 8:05 AM)
8 a.m.
Orals 8:00-8:45
[8:00] Ordering-based Conditions for Global Convergence of Policy Gradient Methods
[8:15] When Demonstrations meet Generative World Models: A Maximum Likelihood Framework for Offline Inverse Reinforcement Learning
[8:30] Online RL in Linearly $q^\pi$-Realizable MDPs Is as Easy as in Linear MDPs If You Learn What to Ignore
(ends 8:45 AM)
Orals 8:00-8:45
[8:00] LeanDojo: Theorem Proving with Retrieval-Augmented Language Models
[8:15] OpenAssistant Conversations - Democratizing Large Language Model Alignment
[8:30] DecodingTrust: A Comprehensive Assessment of Trustworthiness in GPT Models
(ends 8:45 AM)
Orals 8:00-8:45
[8:00] How to Turn Your Knowledge Graph Embeddings into Generative Models
[8:15] Exact Bayesian Inference on Discrete Models via Probability Generating Functions: A Probabilistic Programming Approach
[8:30] Characteristic Circuits
(ends 8:45 AM)
Orals 8:00-8:45
[8:00] Sharpness Minimization Algorithms Do Not Only Minimize Sharpness To Achieve Better Generalization
[8:15] Abide by the law and follow the flow: conservation laws for gradient flows
[8:30] A U-turn on Double Descent: Rethinking Parameter Counting in Statistical Learning
(ends 8:45 AM)
8:45 a.m.
Posters 8:45-10:45
(ends 10:45 AM)
10:45 a.m.
Lunch:
(ends 12:15 PM)
1:05 p.m.
Chairs: Jean Oh · Isabelle Guyon
s 1:05-1:40
[1:05] Kiss/Crash
[1:05] Blabrecs: An AI-Based Game of Nonsense Word Creation
[1:05] Androgynous and Mixed Race Human Face
[1:05] Voice Scroll
[1:05] The WHOOPS! Gallery: An Intersection of AI, Creativity, and the Unusual
[1:05] Visions of Resilience: Augmented Diversity
[1:05] salad bowl
[1:05] AI Applications to Illustrate Native American Arts: Birdsongs: Using Transfer Learning to Augment Image Generation Models
[1:05] Visualising AI
[1:05] Creating playful comics together with AI
(ends 1:40 PM)
1:20 p.m.
Break:
(ends 1:45 PM)
1:40 p.m.
Orals 1:40-2:40
[1:40] Monarch Mixer: A Simple Sub-Quadratic GEMM-Based Architecture
[1:55] QLoRA: Efficient Finetuning of Quantized LLMs
[2:10] Scaling Data-Constrained Language Models
[2:25] Bridging Discrete and Backpropagation: Straight-Through and Beyond
(ends 2:40 PM)
Orals 1:40-2:40
[1:40] Rotating Features for Object Discovery
[1:55] Linguistic Binding in Diffusion Models: Enhancing Attribute Correspondence through Attention Map Alignment
[2:10] Additive Decoders for Latent Variables Identification and Cartesian-Product Extrapolation
[2:25] Emergence of Shape Bias in Convolutional Neural Networks through Activation Sparsity
(ends 2:40 PM)
Orals 1:40-2:40
[1:40] Learning Linear Causal Representations from Interventions under General Nonlinear Mixing
[1:55] A Measure-Theoretic Axiomatisation of Causality
[2:10] Conformal Meta-learners for Predictive Inference of Individual Treatment Effects
[2:25] Causal normalizing flows: from theory to practice
(ends 2:40 PM)
Orals 1:40-2:40
[1:40] Nearly Tight Bounds For Differentially Private Multiway Cut
[1:55] Privacy Auditing with One (1) Training Run
[2:10] Private Everlasting Prediction
[2:25] User-Level Differential Privacy With Few Examples Per User
(ends 2:40 PM)
2:45 p.m.
Break:
(ends 3:30 PM)
3:15 p.m.
Posters 3:15-5:15