ICML 2023

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July 23, 2023 Expo schedule » New in ML »

Timezone: Pacific/Honolulu »

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Time	First Floor Main Lobby	Exhibit Hall 3	Theater 310 Lili' U	Theater 320 Emaline
Sun Jul 23, 2023
10:00 AM (Registration Desks)	Registration
12:30 PM (Expo Talk Panels)			Artificial Generative Innovation – How AI will change how humans innovate
01:30 PM (Expo Talk Panels)			Leveraging Self-Attention Models for Logistics problems in Amazon	Generative AI and Science
02:00 PM (Breaks)		Exhibit Hall Open
03:00 PM (Expo Talk Panels)			Graph Neural Networks in TensorFlow: a Practical Guide	Learning Iconic Scenes with Differential Privacy
05:00 PM (Expo Talk Panels)			Colossal-AI: Breakthroughs in Efficient AI	Vowpal Wabbit: year in review and looking ahead in an LLM world

Time	Ballroom B	Meeting Room 310	Meeting Room 315	First Floor Main Lobby	Exhibit Hall 2	Meeting Room 316 A-C	Exhibit Hall 3
Mon Jul 24, 2023
08:00 AM (Registration Desks)				Registration
08:30 AM (Panels)		ICML Education Outreach Panel
08:45 AM (Affinity Workshops)			LatinX in AI (LXAI) Workshop
09:30 AM (Tutorials)	Reinforcement Learning from Human Feedback: A Tutorial *				Tutorial on Multimodal Machine Learning: Principles, Challenges, and Open Questions	Optimal Transport in Learning, Control, and Dynamical Systems
10:00 AM (Breaks)							Exhibit Hall Open
01:30 PM (Tutorials)	Disinformation, Fake News and Computational Propaganda: Challenges and Opportunities for Machine Learning Research				Self-Supervised Learning in Vision: from Research Advances to Best Practices	How to DP-fy ML: A Practical Tutorial to Machine Learning with Differential Privacy
04:00 PM (Tutorials)	Recent Advances in the Generalization Theory of Neural Networks *				Responsible AI for Generative AI in Practice: Lessons Learned and Open Challenges	Discovering Agent-Centric Latent States in Theory and in Practice
06:15 PM (Receptions)				Welcome Reception
06:30 PM (Receptions)							EXPO Attendee Raffle Prize Give Away

Time	Meeting Room 313	Ballroom B	Ballroom C	Ballroom A	First Floor Main Lobby	Exhibit Hall 2	Meeting Room 316 A-C	Exhibit Hall 3	Exhibit Hall 1	Exhibit Hall 2 with overflow in Exhibit Hall 3
Tue Jul 25, 2023
08:00 AM (Registration Desks)					Registration
09:00 AM (Remarkss)						Opening Remarks
09:15 AM (Invited Talks)										Taking the Pulse Of Ethical ML in Health
10:00 AM (Breaks)								Exhibit Hall Open
11:00 AM (Posters)									Poster Session 1
02:00 PM (Posters)									Poster Session 2
04:00 PM (Invited Talks)										Machine Learning with Social Purpose
05:30 PM (Orals)	Oral A2 Computer Vision and Efficient ML Raising the Cost of Malicious AI-Powered Image Editing	Oral A5 Reinforcement Learning 1 Do the Rewards Justify the Means? Measuring Trade-Offs Between Rewards and Ethical Behavior in the Machiavelli Benchmark	Oral A6 Reinforcement Learning 2 Learning GFlowNets From Partial Episodes For Improved Convergence And Stability	Oral A4 Diffusion AdaptDiffuser: Diffusion Models as Adaptive Self-evolving Planners		Oral A1 Causal Learning, RL, Personalization Bayesian Design Principles for Frequentist Sequential Learning	Oral A3 ML Theory Self-Repellent Random Walks on General Graphs - Achieving Minimal Sampling Variance via Nonlinear Markov Chains
05:38 PM (Orals)	Dynamics-inspired Neuromorphic Visual Representation Learning	Information-Theoretic State Space Model for Multi-View Reinforcement Learning	The Dormant Neuron Phenomenon in Deep Reinforcement Learning	Adversarial Example Does Good: Preventing Painting Imitation from Diffusion Models via Adversarial Examples		Towards Theoretical Understanding of Inverse Reinforcement Learning	Tighter Lower Bounds for Shuffling SGD: Random Permutations and Beyond
05:46 PM (Orals)	Scaling Vision Transformers to 22 Billion Parameters	Reparameterized Policy Learning for Multimodal Trajectory Optimization	Reinforcement Learning from Passive Data via Latent Intentions	Graphically Structured Diffusion Models		On the Power of Pre-training for Generalization in RL: Provable Benefits and Hardness	Which Features are Learnt by Contrastive Learning? On the Role of Simplicity Bias in Class Collapse and Feature Suppression
05:54 PM (Orals)	Facial Expression Recognition with Adaptive Frame Rate based on Multiple Testing Correction	Representation Learning with Multi-Step Inverse Kinematics: An Efficient and Optimal Approach to Rich-Observation RL	Best of Both Worlds Policy Optimization	Diffusion Models as Artists: Are we Closing the Gap between Humans and Machines?		Delayed Feedback in Kernel Bandits	Tighter Information-Theoretic Generalization Bounds from Supersamples
06:02 PM (Orals)	Fourmer: An Efficient Global Modeling Paradigm for Image Restoration	Subequivariant Graph Reinforcement Learning in 3D Environments	Exponential Smoothing for Off-Policy Learning	Refining Generative Process with Discriminator Guidance in Score-based Diffusion Models		Provably Learning Object-Centric Representations	Beyond the Universal Law of Robustness: Sharper Laws for Random Features and Neural Tangent Kernels
06:10 PM (Orals)	Learning Signed Distance Functions from Noisy 3D Point Clouds via Noise to Noise Mapping	A Study of Global and Episodic Bonuses for Exploration in Contextual MDPs	Quantile Credit Assignment	Diffusion Models are Minimax Optimal Distribution Estimators		Task-specific experimental design for treatment effect estimation	Bayes-optimal Learning of Deep Random Networks of Extensive-width
06:18 PM (Orals)	Hiera: A Hierarchical Vision Transformer without the Bells-and-Whistles	Warm-Start Actor-Critic: From Approximation Error to Sub-optimality Gap	Mastering the Unsupervised Reinforcement Learning Benchmark from Pixels	GibbsDDRM: A Partially Collapsed Gibbs Sampler for Solving Blind Inverse Problems with Denoising Diffusion Restoration		Are labels informative in semi-supervised learning? Estimating and leveraging the missing-data mechanism.	Why does Throwing Away Data Improve Worst-Group Error?
06:26 PM (Orals)	Rockmate: an Efficient, Fast, Automatic and Generic Tool for Re-materialization in PyTorch	Efficient RL via Disentangled Environment and Agent Representations	Hierarchies of Reward Machines	OCD: Learning to Overfit with Conditional Diffusion Models		Interventional Causal Representation Learning	Marginalization is not Marginal: No Bad VAE Local Minima when Learning Optimal Sparse Representations
06:34 PM (Orals)	SparseProp: Efficient Sparse Backpropagation for Faster Training of Neural Networks at the Edge	Flipping Coins to Estimate Pseudocounts for Exploration in Reinforcement Learning	Human-Timescale Adaptation in an Open-Ended Task Space	Denoising MCMC for Accelerating Diffusion-Based Generative Models		Returning The Favour: When Regression Benefits From Probabilistic Causal Knowledge	Sharper Bounds for $\ell_p$ Sensitivity Sampling
06:42 PM (Orals)	Fast Inference from Transformers via Speculative Decoding	On the Statistical Benefits of Temporal Difference Learning	Settling the Reward Hypothesis	Cones: Concept Neurons in Diffusion Models for Customized Generation		Sequential Underspecified Instrument Selection for Cause-Effect Estimation	AdaBoost is not an Optimal Weak to Strong Learner
06:50 PM (Orals)							Generalization on the Unseen, Logic Reasoning and Degree Curriculum

Time	Meeting Room 313	Ballroom B	Ballroom C	Ballroom A	Meeting Room 323	Meeting Room 315	First Floor Main Lobby	Exhibit Hall 2	Meeting Room 316 A-C	Exhibit Hall 3	Exhibit Hall 1	Virtual	Exhibit Hall 2 with overflow in Exhibit Hall 3
Wed Jul 26, 2023
08:00 AM (Registration Desks)							Registration
09:30 AM (Invited Talks)													The Future of ML in Biology: CRISPR for Health and Climate
10:00 AM (Breaks)										Exhibit Hall Open
11:00 AM (Posters)											Poster Session 3
02:00 PM (Posters)											Poster Session 4
04:00 PM (Orals, Panels)	Oral B2 Language Models: Algorithms and Architecture Pretraining Language Models with Human Preferences	Oral B5 Self/Semi-Supervised Learning and Interpretability / Observing Aspects of NN RankMe: Assessing the Downstream Performance of Pretrained Self-Supervised Representations by Their Rank	Oral B1 Language Models: Human Impact When Personalization Harms Performance: Reconsidering the Use of Group Attributes in Prediction	Oral B4 Robustness / Adversarial / Rl Bandits Adversarial Policies Beat Superhuman Go AIs				AI and Marginalized Languages	Oral B3 Privacy Nonparametric Extensions of Randomized Response for Private Confidence Sets
04:08 PM (Orals)	Instant Soup: Cheap Pruning Ensembles in A Single Pass Can Draw Lottery Tickets from Large Models	Evaluating Self-Supervised Learning via Risk Decomposition	Pythia: A Suite for Analyzing Large Language Models Across Training and Scaling	Adapting to game trees in zero-sum imperfect information games					Differentially Private Hierarchical Clustering with Provable Approximation Guarantees
04:16 PM (Orals)	Specializing Smaller Language Models towards Multi-Step Reasoning	BEATs: Audio Pre-Training with Acoustic Tokenizers	Whose Opinions Do Language Models Reflect?	Semi Bandit dynamics in Congestion Games: Convergence to Nash Equilibrium and No-Regret Guarantees.					Tight Data Access Bounds for Private Top-$k$ Selection
04:24 PM (Orals)	SparseGPT: Massive Language Models Can be Accurately Pruned in One-Shot	Efficient Self-supervised Learning with Contextualized Target Representations for Vision, Speech and Language	A Watermark for Large Language Models	Delving into Noisy Label Detection with Clean Data					JAWS-X: Addressing Efficiency Bottlenecks of Conformal Prediction Under Standard and Feedback Covariate Shift
04:32 PM (Orals)	Arithmetic Sampling: Parallel Diverse Decoding for Large Language Models	Bidirectional Adaptation for Robust Semi-Supervised Learning with Inconsistent Data Distributions	DetectGPT: Zero-Shot Machine-Generated Text Detection using Probability Curvature	Robustly Learning a Single Neuron via Sharpness					Active Ranking of Experts Based on their Performances in Many Tasks
04:40 PM (Orals)	FlexGen: High-Throughput Generative Inference of Large Language Models with a Single GPU	TRAK: Attributing Model Behavior at Scale	Using Large Language Models to Simulate Multiple Humans and Replicate Human Subject Studies	Data Feedback Loops: Model-driven Amplification of Dataset Biases					The Price of Differential Privacy under Continual Observation
04:48 PM (Orals)	BPipe: Memory-Balanced Pipeline Parallelism for Training Large Language Models	Understanding Plasticity in Neural Networks	Inflow, Outflow, and Reciprocity in Machine Learning	Towards Reliable Neural Specifications					HETAL: Efficient Privacy-preserving Transfer Learning with Homomorphic Encryption
04:56 PM (Orals)	Tractable Control for Autoregressive Language Generation	Fundamental Limits of Two-layer Autoencoders, and Achieving Them with Gradient Methods	Structure-informed Language Models Are Protein Designers	Do Perceptually Aligned Gradients Imply Robustness?					Sketch-Flip-Merge: Mergeable Sketches for Private Distinct Counting
05:04 PM (Orals)	Equivariant Architectures for Learning in Deep Weight Spaces	Random Classification Noise does not defeat All Convex Potential Boosters Irrespective of Model Choice	Transformers Learn In-Context by Gradient Descent	ODS: Test-Time Adaptation in the Presence of Open-World Data Shift					Fast Private Kernel Density Estimation via Locality Sensitive Quantization
05:12 PM (Orals)		Brauer's Group Equivariant Neural Networks		Analysis of Error Feedback in Federated Non-Convex Optimization with Biased Compression: Fast Convergence and Partial Participation					Multi-Epoch Matrix Factorization Mechanisms for Private Machine Learning
05:45 PM (Socials, Town Halls)	Black in AI	ICML Business Meeting - all attendees	Information Theory at ICML: A Confluence of Minds	How to Know Your True Market Value as an AI Researcher	ML Safety Social	ML in Korea
07:00 PM (Socials)												Social for Virtual Participants

Time	Meeting Room 313	Ballroom B	Ballroom C	Ballroom A	Meeting Room 315	Meeting Room 314	First Floor Main Lobby	Exhibit Hall 2	Meeting Room 316 A-C	Concourse Foyer Level 3 Ala Halawai	Exhibit Hall 1
Thu Jul 27, 2023
08:00 AM (Registration Desks)							Registration
08:30 AM (Test Of Times)								Learning Fair Representations
09:30 AM (Invited Talks)								Proxy objectives in reinforcement learning from human feedback
10:30 AM (Posters)											Poster Session 5
01:30 PM (Posters)											Poster Session 6
03:00 PM (Orals, Panels)	Oral C1 Supervised Learning Mimetic Initialization of Self-Attention Layers	Oral C4 Optimization Second-Order Optimization with Lazy Hessians	Oral C5 Misc Learning Mixtures of Markov Chains and MDPs	Oral C3 Multimodal and Pretaining Pix2Struct: Screenshot Parsing as Pretraining for Visual Language Understanding				The Societal Impacts of AI	Oral C2 Time Series / Dynamics / Sequences Neural Continuous-Discrete State Space Models for Irregularly-Sampled Time Series
03:08 PM (Orals)	Difference of submodular minimization via DC programming	Unifying Nesterov's Accelerated Gradient Methods for Convex and Strongly Convex Objective Functions	Uncertain Evidence in Probabilistic Models and Stochastic Simulators	Calibrating Multimodal Learning					Self-Interpretable Time Series Prediction with Counterfactual Explanations
03:16 PM (Orals)	Simplex Random Features	Transformer-based Stagewise Decomposition for Large-Scale Multistage Stochastic Optimization	How Bad is Top-$K$ Recommendation under Competing Content Creators?	StyleGAN-T: Unlocking the Power of GANs for Fast Large-Scale Text-to-Image Synthesis					Resurrecting Recurrent Neural Networks for Long Sequences
03:24 PM (Orals)	Patch-level Routing in Mixture-of-Experts is Provably Sample-efficient for Convolutional Neural Networks	Continuation Path Learning for Homotopy Optimization	Weighted Flow Diffusion for Local Graph Clustering with Node Attributes: an Algorithm and Statistical Guarantees	ProtST: Multi-Modality Learning of Protein Sequences and Biomedical Texts					Inferring Relational Potentials in Interacting Systems
03:32 PM (Orals)	Tilted Sparse Additive Models	Over-parametrization via Lifting for Low-rank Matrix Sensing: Conversion of Spurious Solutions to Strict Saddle Points	Equivariant Polynomials for Graph Neural Networks	Cross-Modal Fine-Tuning: Align then Refine					Memory-Based Dual Gaussian Processes for Sequential Learning
03:40 PM (Orals)	Dynamic Regularized Sharpness Aware Minimization in Federated Learning: Approaching Global Consistency and Smooth Landscape	Buying Information for Stochastic Optimization	Taming graph kernels with random features	Mu$^2$SLAM: Multitask, Multilingual Speech and Language Models					H-Likelihood Approach to Deep Neural Networks with Temporal-Spatial Random Effects for High-Cardinality Categorical Features
03:48 PM (Orals)	Hyena Hierarchy: Towards Larger Convolutional Language Models	A Fully First-Order Method for Stochastic Bilevel Optimization	Robust Budget Pacing with a Single Sample	Deja Vu: Contextual Sparsity for Efficient LLMs at Inference Time					Generalized Teacher Forcing for Learning Chaotic Dynamics
03:56 PM (Orals)	Direct Parameterization of Lipschitz-Bounded Deep Networks	Practical and Matching Gradient Variance Bounds for Black-Box Variational Bayesian Inference	Multicalibration as Boosting for Regression	Pre-training for Speech Translation: CTC Meets Optimal Transport					Gaussian Process Priors for Systems of Linear Partial Differential Equations with Constant Coefficients
04:04 PM (Orals)		Learning-Rate-Free Learning by D-Adaptation		Same Pre-training Loss, Better Downstream: Implicit Bias Matters for Language Models					Spherical Fourier Neural Operators: Learning Stable Dynamics on the Sphere
04:12 PM (Orals)	Subsample Ridge Ensembles: Equivalences and Generalized Cross-Validation			Spherical Inducing Features for Orthogonally-Decoupled Gaussian Processes					Learning Control-Oriented Dynamical Structure from Data
04:30 PM (Receptions)										Closing Reception
05:45 PM (Socials)	Early Career Researchers Social	The Role of Generative AI in Shaping the Next Generation of the Metaverse	Inclusive AI: Magnifying Marginalized Communities	Behind the buzzwords. Humans...	Unleashing the Power of AI-Enabled Digital Twins	AI Data Underground DMLR Social - Discussing Data-centric Machine Learning Research

Time	Meeting Room 313	Ballroom B	Ballroom C	Ballroom A	Meeting Room 311	Meeting Room 323	Meeting Room 310	Meeting Room 315	Meeting Room 312	Meeting Room 320	Meeting Room 314	Meeting Room 301	Meeting Room 317 B	Meeting Room 317 A	Meeting Room 316 AB	Meeting Room 316C	First Floor Main Lobby
Fri Jul 28, 2023
08:00 AM (Registration Desks)																	Registration
08:50 AM (Workshops)				2nd ICML Workshop on New Frontiers in Adversarial Machine Learning
08:55 AM (Workshops)														Workshop on Theory of Mind in Communicating Agents
09:00 AM (Workshops)	Challenges in Deployable Generative AI	New Frontiers in Learning, Control, and Dynamical Systems			Federated Learning and Analytics in Practice: Algorithms, Systems, Applications, and Opportunities	Structured Probabilistic Inference and Generative Modeling	Differentiable Almost Everything: Differentiable Relaxations, Algorithms, Operators, and Simulators	HiLD: High-dimensional Learning Dynamics Workshop	2nd Workshop on Formal Verification of Machine Learning	The Synergy of Scientific and Machine Learning Modelling (SynS & ML) Workshop	PAC-Bayes Meets Interactive Learning	Knowledge and Logical Reasoning in the Era of Data-driven Learning	2nd Annual Workshop on Topology, Algebra, and Geometry in Machine Learning (TAG-ML)		The Many Facets of Preference-Based Learning
09:15 AM (Affinity Workshops, Workshops)			3rd Workshop on Interpretable Machine Learning in Healthcare (IMLH)													4th Women in Machine Learning (WiML) Un-Workshop

Time	Meeting Room 313	Ballroom B	Ballroom C	Ballroom A	Meeting Room 311	Meeting Room 323	Meeting Room 310	Meeting Room 315	Meeting Room 312	Meeting Room 320	Meeting Room 314	Meeting Room 301	Meeting Room 317 B	Meeting Room 317 A	Meeting Room 316 AB	Meeting Room 316C	First Floor Main Lobby
Sat Jul 29, 2023
08:00 AM (Registration Desks)																	Registration
08:50 AM (Workshops)															The Second Workshop on Spurious Correlations, Invariance and Stability
08:55 AM (Workshops)				ES-FoMo: Efficient Systems for Foundation Models
09:00 AM (Workshops)	Neural Conversational AI Workshop - What’s left to TEACH (Trustworthy, Enhanced, Adaptable, Capable and Human-centric) chatbots?	Generative AI and Law (GenLaw)	DMLR Workshop: Data-centric Machine Learning Research		Artificial Intelligence & Human Computer Interaction	Machine Learning for Multimodal Healthcare Data	Localized Learning: Decentralized Model Updates via Non-Global Objectives	Interactive Learning with Implicit Human Feedback	Sampling and Optimization in Discrete Space	Duality Principles for Modern Machine Learning	ICML 2023 Workshop on Computational Biology	“Could it have been different?” Counterfactuals in Minds and Machines	2nd ICML Workshop on Machine Learning for Astrophysics	Neural Compression: From Information Theory to Applications
09:15 AM (Affinity Workshops)																Indigenous in AI Workshop