Name: Learning from Societal Data: Theory and Practice
Start: 2020-03-31T12:00:00-04:00
End: 2020-03-31T13:00:00-04:00
Location: Remote/Virtual

Mar 21

10:30 am - 11:30 am

Translating AI to Impact: Uncertainty and Human-agent Interactions in Multi-agent Systems for Public Health and Conservation

3725 Beyster Building 2260 Hayward Street, Ann Arbor

Event Details Get Directions

Events

Building Robust Systems Through System-Memory Co-Design

Empowering Users on Social Media for Better Content Credibility

Analyzing and Securing Software via Robust and Generalizable Learning

Theoretical Foundations and Design Methodologies for Cyber-Neural Systems: a Case Study in Epilepsy

Designing Provably Performant Networked Systems

Enabling Compositional Generalization of AI Systems

Reinforcement Learning from Static Datasets: Algorithms, Analysis and Applications

Looking Past the Abstractions: Characterizing Information Flow in Real-World Systems

Interactive and Grounded Language Learning

Building Sustainable Computational Materials

Socially Responsible and Factual Reasoning for Equitable AI Systems

Software and Architecture for Reliable Quantum Computing

Self-Supervised Reinforcement Learning

The Gale-Shapley Algorithm

Rethinking System Design for Expressive Cryptography

Fire! Sensing Smoke Across the US using Multiple Linear Regression

Binary Search Trees

Database Concepts

Teaching Demonstration (Hashtables)

Introduction to Dynamic Programming

First Look at Binary Search Trees

Prediction, Causality and the Great In-between

Faster, smarter, and greener systems for data-center scale AI

Learning to Generate Data by Estimating Gradients of the Data Distribution

Beyond ISAs: Striking a Balance between Generality and Specialization for AI/ML

Unleashing the Potential of In-Network Computing

Towards a Foundation for Reinforcement Learning

Machine Learning Powered Query Optimization

Optimizing CPU Efficiency and Tail Latency in Datacenters

Formal Verification of a Concurrent File System

Efficient and Accurate Systems for Querying Unstructured Data

Putting Your Database on Autopilot: Self-driving Database Management Systems

Translating AI to Impact: Uncertainty and Human-agent Interactions in Multi-agent Systems for Public Health and Conservation

From Specialists to Generalists: Inductive Biases of Deep Learning for Higher Level Cognition

Grounding Language by Seeing, Hearing, and Interacting

Consistency and Performance in Distributed Storage Systems

Towards Scalable Representation Learning for Visual Recognition

Advancing Quantum Science with Ytterbium Atom Arrays

Verifiable Machine Learning for Security

Emerging Optics from Structured Nanomaterials

Co-designing Distributed Systems and Storage Stacks for Improved Reliability

Processor Microarchitecture Security

The Complexity of Near-Term Quantum Computers

AI-powered Computational Imaging and Processing for Advancing Visualization and Perception in Biomedical Applications

Learning to address novel situations through human-robot collaboration

Empowering People to Have Secure and Private Interactions with Digital Technologies

Introduction to Data Science

Matching in Evolving Environments

Architecting Emerging Quantum Technologies

Advancing Sound Accessibility

Theoretical Foundations for Emerging Multiprocessor Hardware

Quantum Computation and Cryptography: a changing landscape

Computing Using Time

Theoretical Foundations of Pre-trained Models

Teaching Faculty Candidate Seminar: Gerald Soosai Raj

Teaching Faculty Candidate Seminar–Gina Bai

Teaching Faculty Candidate Seminar–Elba Garza

Teaching Faculty Candidate Seminar: Alan Weide

Teaching Faculty Candidate Seminar: Saquib Razak

Compositional Reasoning in Robot Learning

Bridging Algorithmic and Statistical Randomness in Machine Learning

IDEs for Ideas

Enabling Hyperscale Web Services

SAUL: Towards Effective Data Science

Architecting Quantum Computing Systems in the Presence of Noise

Learning to See the 3D world

Eliminating Bugs in Real Systems

Sample-Efficient Nonconvex Optimization Algorithms for Machine Learning

Steps towards making machine learning more natural

Perception and Decision-Making Systems for Human-Robot Teaming in Safety-Critical Environments

Physics-Based Visual Computing for Efficient 3D Vision and Sensing

Diversity and Fairness in Data Summarization Algorithms

Probabilistic proofs: theory, hardware, and everything in between

Artificial Intelligence for Geometry Processing

Defining and Ensuring Algorithmic Fairness in Artificial Intelligence

Opening the Black Box: Towards Theoretical Understanding of Deep Learning

Fair and Reliable Machine Learning for High-Stakes Applications: Approaches Using Information Theory

Physically Interactive Intelligence — A path towards autonomous embodied agents

Developing and Deploying Gallium Nitride Magnetometers for Harsh Environments