b'Ahmad Beirami'

research

∙ 07/24/2023

A Systematic Survey of Prompt Engineering on Vision-Language Foundation Models

Prompt engineering is a technique that involves augmenting a large pre-t...

0 Jindong Gu, et al. ∙

research

∙ 07/11/2023

Towards A Scalable Solution for Improving Multi-Group Fairness in Compositional Classification

Despite the rich literature on machine learning fairness, relatively lit...

0 James Atwood, et al. ∙

research

∙ 06/25/2023

Let's Do a Thought Experiment: Using Counterfactuals to Improve Moral Reasoning

Language models still struggle on moral reasoning, despite their impress...

0 Xiao Ma, et al. ∙

research

∙ 06/03/2023

Uncovering the Hidden Dynamics of Video Self-supervised Learning under Distribution Shifts

Video self-supervised learning (VSSL) has made significant progress in r...

0 Pritam Sarkar, et al. ∙

research

∙ 04/17/2023

Towards Robust Prompts on Vision-Language Models

With the advent of vision-language models (VLMs) that can perform in-con...

0 Jindong Gu, et al. ∙

research

∙ 12/15/2021

Database Search Results Disambiguation for Task-Oriented Dialog Systems

As task-oriented dialog systems are becoming increasingly popular in our...

0 Kun Qian, et al. ∙

research

∙ 12/15/2021

CheckDST: Measuring Real-World Generalization of Dialogue State Tracking Performance

Recent neural models that extend the pretrain-then-finetune paradigm con...

3 Hyundong Cho, et al. ∙

research

∙ 11/08/2021

Information-Theoretic Bayes Risk Lower Bounds for Realizable Models

We derive information-theoretic lower bounds on the Bayes risk and gener...

30 Matthew Nokleby, et al. ∙

research

∙ 10/28/2021

FeO2: Federated Learning with Opt-Out Differential Privacy

Federated learning (FL) is an emerging privacy-preserving paradigm, wher...

0 Nasser Aldaghri, et al. ∙

research

∙ 10/21/2021

DAIR: Data Augmented Invariant Regularization

While deep learning through empirical risk minimization (ERM) has succee...

0 Tianjian Huang, et al. ∙

research

∙ 09/13/2021

On Tilted Losses in Machine Learning: Theory and Applications

Exponential tilting is a technique commonly used in fields such as stati...

0 Tian Li, et al. ∙

research

∙ 05/29/2021

Annotation Inconsistency and Entity Bias in MultiWOZ

MultiWOZ is one of the most popular multi-domain task-oriented dialog da...

0 Kun Qian, et al. ∙

research

∙ 02/24/2021

FERMI: Fair Empirical Risk Minimization via Exponential Rényi Mutual Information

In this paper, we propose a new notion of fairness violation, called Exp...

0 Andrew Lowy, et al. ∙

research

∙ 01/01/2021

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

A video-grounded dialogue system is required to understand both dialogue...

1 Hung Le, et al. ∙

research

∙ 12/31/2020

Coded Machine Unlearning

Models trained in machine learning processes may store information about...

0 Nasser Aldaghri, et al. ∙

research

∙ 12/08/2020

Federated Multi-Task Learning for Competing Constraints

In addition to accuracy, fairness and robustness are two critical concer...

0 Tian Li, et al. ∙

research

∙ 11/12/2020

Overview of the Ninth Dialog System Technology Challenge: DSTC9

This paper introduces the Ninth Dialog System Technology Challenge (DSTC...

4 Chulaka Gunasekara, et al. ∙

research

∙ 11/10/2020

Resource Constrained Dialog Policy Learning via Differentiable Inductive Logic Programming

Motivated by the needs of resource constrained dialog policy learning, w...

0 Zhenpeng Zhou, et al. ∙

research

∙ 08/28/2020

Centralized vs Decentralized Targeted Brute-Force Attacks: Guessing with Side-Information

According to recent empirical studies, a majority of users have the same...

0 Salman Salamatian, et al. ∙

research

∙ 07/02/2020

Tilted Empirical Risk Minimization

Empirical risk minimization (ERM) is typically designed to perform well ...

0 Tian Li, et al. ∙

research

∙ 06/24/2020

Competitive Balance in Team Sports Games

Competition is a primary driver of player satisfaction and engagement in...

7 Sofia M Nikolakaki, et al. ∙

research

∙ 06/02/2020

Situated and Interactive Multimodal Conversations

Next generation virtual assistants are envisioned to handle multimodal i...

8 Seungwhan Moon, et al. ∙

research

∙ 07/04/2019

Bayesian Nonlinear Function Estimation with Approximate Message Passing

In many areas, massive amounts of data are collected and analyzed in ord...

0 Hangjin Liu, et al. ∙

research

∙ 07/01/2019

Mismatched Guesswork

We study the problem of mismatched guesswork, where we evaluate the numb...

0 Salman Salamatian, et al. ∙

research

∙ 06/25/2019

On Multi-Agent Learning in Team Sports Games

In recent years, reinforcement learning has been successful in solving v...

0 Yunqi Zhao, et al. ∙

research

∙ 06/03/2019

Towards Interactive Training of Non-Player Characters in Video Games

There is a high demand for high-quality Non-Player Characters (NPCs) in ...

0 Igor Borovikov, et al. ∙

research

∙ 03/25/2019

Winning Isn't Everything: Enhancing Game Development with Intelligent Agents

Recently, there have been several high-profile achievements of agents le...

0 Yunqi Zhao, et al. ∙

research

∙ 03/25/2019

Winning Isn't Everything: Training Human-Like Agents for Playtesting and Game AI

Recently, there have been several high-profile achievements of agents le...

0 Yunqi Zhao, et al. ∙

research

∙ 01/11/2019

Universal Compression with Side Information from a Correlated Source

Packets originated from an information source in the network can be high...

0 Ahmad Beirami, et al. ∙

research

∙ 10/26/2018

Information Bottleneck Methods for Distributed Learning

We study a distributed learning problem in which Alice sends a compresse...

0 Parinaz Farajiparvar, et al. ∙

research

∙ 05/29/2018

Why Botnets Work: Distributed Brute-Force Attacks Need No Synchronization

In September 2017, McAffee Labs quarterly report estimated that brute fo...

0 Salman Salamatian, et al. ∙

research

∙ 01/27/2018

A Characterization of Guesswork on Swiftly Tilting Curves

Given a collection of strings, each with an associated probability of oc...

0 Ahmad Beirami, et al. ∙

research

∙ 12/25/2017

Guesswork Subject to a Total Entropy Budget

We consider an abstraction of computational security in password protect...

0 Arman Rezaee, et al. ∙

research

∙ 12/19/2017

On Data-Dependent Random Features for Improved Generalization in Supervised Learning

The randomized-feature approach has been successfully employed in large-...

0 Shahin Shahrampour, et al. ∙

research

∙ 11/14/2017

On Optimal Generalizability in Parametric Learning

We consider the parametric learning problem, where the objective of the ...

0 Ahmad Beirami, et al. ∙

research

∙ 05/08/2016

Rate-Distortion Bounds on Bayes Risk in Supervised Learning

We present an information-theoretic framework for bounding the number of...

0 Matthew Nokleby, et al. ∙

Ahmad Beirami

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