Publications

Publication

October 01, 2021

COMPUTER VISION

CONVERSATIONAL AI

DVD: A Diagnostic Dataset for Multi-step Reasoning in Video Grounded Dialogue

A video-grounded dialogue system is required to understand both dialogue, which contains semantic dependencies from turn to turn …

Hung Le, Chinnadhurai Sankar, Seungwhan Moon, Ahmad Beiram, Alborz Geramifard, Satwik Kottur

October 01, 2021

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Publication

August 29, 2021

NLP

Many-Speakers Single Channel Speech Separation with Optimal Permutation Training

Single channel speech separation has experienced great progress in the last few years …

Shaked Dovrat,Eliya Nachmani, Lior Wolf

August 29, 2021

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Publication

August 09, 2021

COMPUTER VISION

GRAPHICS

Deep Relightable Appearance Models for Animatable Faces

We present a method for building high-fidelity animatable 3D face models that can be posed and rendered with novel lighting environments in real-time. …

Sai Bi, Stephen Lombardi,Shunsuke Saito, Tomas Simon, Shih-en Wei, Kevyn McPhail, Ravi Ramamoorthi, Yaser Sheikh, Jason Saragih

August 09, 2021

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Publication

August 09, 2021

GRAPHICS

COMPUTER VISION

Control Strategies for Physically Simulated Characters Performing Two-player Competitive Sports

In two-player competitive sports, such as boxing and fencing, athletes often demonstrate efficient and tactical movements during a competition …

Jungdam Won, Deepak Gopinath, Jessica Hodgins

August 09, 2021

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Publication

August 01, 2021

GRAPHICS

COMPUTER VISION

Evaluation Examples Are Not Equally Informative: How Should That Change NLP Leaderboards?

Leaderboards are widely used in NLP and push the field forward. While leaderboards are a straightforward ranking of NLP models, this simplicity can mask nuances in evaluation items …

Pedro Rodriguez, Joe Barrow, Alexander Hoyle, John P. Lalor, Robin Jia, Jordan Boyd-Graber

August 01, 2021

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Publication

August 01, 2021

GRAPHICS

COMPUTER VISION

Phase Transitions, Distance Functions, and Implicit Neural Representations

Representing surfaces as zero level sets of neural networks recently emerged as a powerful modeling paradigm, named Implicit Neural Representations (INRs) …

Yaron Lipman

August 01, 2021

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Publication

July 24, 2021

CORE MACHINE LEARNING

Ditto: Fair and Robust Federated Learning Through Personalization

Fairness and robustness are two important concerns for federated learning systems. In this work, we identify that robustness to data and model …

Tian Li, Shengyuan Hu, Ahmad Beirami, Virginia Smith

July 24, 2021

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Publication

July 24, 2021

THEORY

CORE MACHINE LEARNING

Using Bifurcations for Diversity in Differentiable Games

Ridge Rider (RR) is an algorithm for finding diverse solutions to optimization problems by following eigenvectors …

Jonathan Lorraine, Jack Parker-Holder, Paul Vicol, Aldo Pacchiano, Luke Metz, Tal Kachman, Jakob Foerster

July 24, 2021

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Publication

July 24, 2021

CORE MACHINE LEARNING

SYSTEMS RESEARCH

Federated Learning with Buffered Asynchronous Aggregation

Federated Learning (FL) trains a shared model across distributed devices while keeping the training data on the devices. …

John Nguyen, Kshitiz Malik, Hongyuan Zhan, Ashkan Yousefpour, Michael Rabbat, Mani Malek, Dzmitry Huba

July 24, 2021

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Publication

July 18, 2021

CORE MACHINE LEARNING

Marginalized Stochastic Natural Gradients for Black-Box Variational Inference

Black-box variational inference algorithms use stochastic sampling to analyze diverse statistical models, like those expressed in probabilistic programming languages …