Name: Game Playing Meets Game Theory: Strategic Learning from Simulated Play
Start: 2019-09-24T16:00:00-04:00
End: 2019-09-24T17:15:00-04:00
Location: 3725 Beyster Building

Jan 30

4:00 pm - 5:00 pm

Realizing AI for Impact: Uncertainty and Human-Agent Collaboration in Multi-Agent Systems for Public Health and Conservation

3725 Beyster Building 2260 Hayward Street, Ann Arbor

Event Details Get Directions

Events

AI for Social Impact: Deployed Resource Optimization and Future Acceleration with Foundation Models

Generative Models of Video

Optimizing for Long-Term Vision in a Fast-Paced Research World

Executable and Trustworthy Planning with Large Language Models

The Computational Gauntlet of Human-Like Learning

Harnessing collaborative intelligence in the Post-LLM world

Personal Assistive Technology

Small Hybrid Language Model

Leveraging AI to Address Poverty-related Issues

Web Agents: A New Frontier for Embodied Agents

The Next Big Thing in A.I.

Building a Unicorn Startup and Accelerating Innovation with AI Physics

Knowledge-guided Machine Learning

Broadening Perspectives on African Governance in the Age of AI

Weight Space Learning: Learning Representations of Populations of Neural Networks

The Future is Hear: Innovations from the Interactive Audio Lab

AI Lab Idea Snippets

Scalable Real-time Abnormal Event Detection

Sparse Feature Circuits: Discovering and Editing Interpretable Causal Graphs in Language Models

Leveraging Formal Methods for Trustworthy AI-assisted Software Development

Ethical AI in Healthcare

On Building General-Purpose Home Robots

Towards a Science of Human-AI Decision Making: Empirical Understandings, Computational Models, and Intervention Designs

From Autonomy to Synergy: Envisioning Next Generation Human-AI Partnerships

Realizing AI for Impact: Uncertainty and Human-Agent Collaboration in Multi-Agent Systems for Public Health and Conservation

Strategic Reasoning in Machine Learning, with Implications for Security and Fairness

Code Representation Learning at Scale

Data-driven Solutions for Blood Glucose Management

Bridging AI, Data, and Epidemiological Models

Automatically Capturing and Reflecting Latent Label Dependencies in Machine Learning Models

Human-Centered Artificial Intelligence at Howard University

Interaction Design Challenges for AI in Medicine

Learning Syntactic Structures from Visually Grounded Text and Speech

Recent Advancements in Quantization, Pruning and Knowledge Distillation

Task Planning with Large Language Models

Answering Why Questions about Narrative Text

Learning to Re-create Reality in 3D

Postcards from the Future

Measuring and Improving the Internal Conceptual Representations of Deep Learning

Effective and Efficient Knowledge-Intensive NLP

Preparing for Your Industrial Job Search

Exploiting Domain Knowledge and Modular Semantics in Deep Learning for Natural Language Comprehension and Grounding

A Defense of (Empirical) Neural Tangent Kernels

Confounding-Robust Policy Learning under Sequentially Exogenous Unobserved Confounders

AI Seminar: Stella Yu – Unsupervised Data-Driven Learning of Visual Hierarchy

AI Seminar: Iryna Gurevych – Comment – Link – Revise: Towards a General Framework for Modelling Interconnected Texts

AI Seminar: David Jurgens – Does chocolate really cure cancer? Modeling Information Change in Science Communication

AI Seminar: Con Slobodchikoff – Decoding Animal Languages: Possibilities and Challenges

AI Seminar: Benjamin Kuipers – AI, Ethics, Trust, Cooperation & Society

AI Seminar: Rada Mihalcea – The Ups and Downs of Word Embeddings

Bringing Ethics and Justice into CS Courses: The Social and Political Factors at Play in Entry-Level CS Concepts

Human-Centered Explainable AI (XAI): From Algorithms to User Experiences

Algorithmic Gaussianization in Machine Learning

Defining cellular identity from single-cell genomic data with machine learning

Expanding the frontiers of AI – Applications in Environmental Conservation and Health

Neural Architecture

Inference and the “Racial Drama” of AI

Knowledge-enhanced Text Generation: The Curious Case of Figurative Language and Argumentation

The facebook files at training time: incentivizing discrimination in machine learning

Continual Language Learning through Collaborative Interaction with Users

Machine Learning and Causality: Building Efficient, Reliable Models for Decision-Making

Jitendra Malik | Where Do We Come From, What Are We Doing, Where Are We Going

Danielle Belgrave | ML for Personalized Mental Healthcare

Pascale Fung | Deeper Conversational AI

Learning sight from sound

Distortion-based Analysis of Voting: Limited Communication, and an Analysis Framework based on LP Duality and Flows

NumPy: A look at the past, present, and future of array computation

Language Grounding in Situated Communication