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07/30/2023
AI Increases Global Access to Reliable Flood Forecasts
Floods are one of the most common and impactful natural disasters, with ...
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06/01/2023
Using generative AI to investigate medical imagery models and datasets
AI models have shown promise in many medical imaging tasks. However, our...
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05/31/2023
Factually Consistent Summarization via Reinforcement Learning with Textual Entailment Feedback
Despite the seeming success of contemporary grounded text generation sys...
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03/22/2023
Leximin Approximation: From Single-Objective to Multi-Objective
Leximin is a common approach to multi-objective optimization, frequently...
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07/25/2022
Dynamic Planning in Open-Ended Dialogue using Reinforcement Learning
Despite recent advances in natural language understanding and generation...
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04/11/2022
TRUE: Re-evaluating Factual Consistency Evaluation
Grounded text generation systems often generate text that contains factu...
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11/04/2021
Flood forecasting with machine learning models in an operational framework
The operational flood forecasting system by Google was developed to prov...
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06/28/2021
Adversarial Robustness of Streaming Algorithms through Importance Sampling
In this paper, we introduce adversarially robust streaming algorithms fo...
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04/27/2021
Explaining in Style: Training a GAN to explain a classifier in StyleSpace
Image classification models can depend on multiple different semantic at...
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11/29/2020
ML-based Flood Forecasting: Advances in Scale, Accuracy and Reach
Floods are among the most common and deadly natural disasters in the wor...
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06/20/2020
An Optimal Elimination Algorithm for Learning a Best Arm
We consider the classic problem of (ϵ,δ)-PAC learning a best arm where t...
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04/13/2020
Adversarially Robust Streaming Algorithms via Differential Privacy
A streaming algorithm is said to be adversarially robust if its accuracy...
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10/27/2019
Spectral Algorithm for Low-rank Multitask Regression
Multitask learning, i.e. taking advantage of the relatedness of individu...
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07/31/2019
Personalizing ASR for Dysarthric and Accented Speech with Limited Data
Automatic speech recognition (ASR) systems have dramatically improved ov...
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03/17/2019
Audio De-identification: A New Entity Recognition Task
Named Entity Recognition (NER) has been mostly studied in the context of...
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02/13/2019
Learning and Generalization for Matching Problems
We study a classic algorithmic problem through the lens of statistical l...
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01/28/2019
ML for Flood Forecasting at Scale
Effective riverine flood forecasting at scale is hindered by a multitude...
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01/03/2019
Towards Global Remote Discharge Estimation: Using the Few to Estimate The Many
Learning hydrologic models for accurate riverine flood prediction at sca...
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06/19/2018
Online Linear Quadratic Control
We study the problem of controlling linear time-invariant systems with k...
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05/07/2018
Planning and Learning with Stochastic Action Sets
In many practical uses of reinforcement learning (RL) the set of actions...
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04/10/2018
Looking to Listen at the Cocktail Party: A Speaker-Independent Audio-Visual Model for Speech Separation
We present a joint audio-visual model for isolating a single speech sign...
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03/14/2018
LSH Microbatches for Stochastic Gradients: Value in Rearrangement
Metric embeddings are immensely useful representation of interacting ent...
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12/19/2017
MUDA: A Truthful Multi-Unit Double-Auction Mechanism
In a seminal paper, McAfee (1992) presented a truthful mechanism for dou...
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11/19/2017
Truthful Bilateral Trade is Impossible even with Fixed Prices
A seminal theorem of Myerson and Satterthwaite (1983) proves that, in a ...
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01/12/2016