Manuela Veloso

research

∙ 08/22/2023

Exploring the Effectiveness of GPT Models in Test-Taking: A Case Study of the Driver's License Knowledge Test

Large language models such as Open AI's Generative Pre-trained Transform...

0 Saba Rahimi, et al. ∙

research

∙ 07/17/2023

Towards Accelerating Benders Decomposition via Reinforcement Learning Surrogate Models

Stochastic optimization (SO) attempts to offer optimal decisions in the ...

0 Stephen Mak, et al. ∙

research

∙ 06/19/2023

Differentially Private Synthetic Data Using KD-Trees

Creation of a synthetic dataset that faithfully represents the data dist...

0 Eleonora Kreačić, et al. ∙

research

∙ 04/11/2023

Financial Time Series Forecasting using CNN and Transformer

Time series forecasting is important across various domains for decision...

0 Zhen Zeng, et al. ∙

research

∙ 12/12/2022

Fast Learning of Multidimensional Hawkes Processes via Frank-Wolfe

Hawkes processes have recently risen to the forefront of tools when it c...

0 Renbo Zhao, et al. ∙

research

∙ 11/21/2022

Learn to explain yourself, when you can: Equipping Concept Bottleneck Models with the ability to abstain on their concept predictions

The Concept Bottleneck Models (CBMs) of Koh et al. [2020] provide a mean...

0 Joshua Lockhart, et al. ∙

research

∙ 11/07/2022

Towards learning to explain with concept bottleneck models: mitigating information leakage

Concept bottleneck models perform classification by first predicting whi...

0 Joshua Lockhart, et al. ∙

research

∙ 10/13/2022

Towards Multi-Agent Reinforcement Learning driven Over-The-Counter Market Simulations

We study a game between liquidity provider and liquidity taker agents in...

0 Nelson Vadori, et al. ∙

research

∙ 09/30/2022

ASPiRe:Adaptive Skill Priors for Reinforcement Learning

We introduce ASPiRe (Adaptive Skill Prior for RL), a new approach that l...

0 Mengda Xu, et al. ∙

research

∙ 08/16/2022

Online Learning for Mixture of Multivariate Hawkes Processes

Online learning of Hawkes processes has received increasing attention in...

12 Mohsen Ghassemi, et al. ∙

research

∙ 07/27/2022

Differentially Private Learning of Hawkes Processes

Hawkes processes have recently gained increasing attention from the mach...

2 Mohsen Ghassemi, et al. ∙

research

∙ 02/17/2022

A Survey of Explainable Reinforcement Learning

Explainable reinforcement learning (XRL) is an emerging subfield of expl...

35 Stephanie Milani, et al. ∙

research

∙ 01/11/2022

Structure with Semantics: Exploiting Document Relations for Retrieval

Retrieving relevant documents from a corpus is typically based on the se...

0 Natraj Raman, et al. ∙

research

∙ 12/06/2021

Simulation Intelligence: Towards a New Generation of Scientific Methods

The original "Seven Motifs" set forth a roadmap of essential methods for...

50 Alexander Lavin, et al. ∙

research

∙ 11/11/2021

Synthetic Document Generator for Annotation-free Layout Recognition

Analyzing the layout of a document to identify headers, sections, tables...

6 Natraj Raman, et al. ∙

research

∙ 10/27/2021

ABIDES-Gym: Gym Environments for Multi-Agent Discrete Event Simulation and Application to Financial Markets

Model-free Reinforcement Learning (RL) requires the ability to sample tr...

9 Selim Amrouni, et al. ∙

research

∙ 10/27/2021

Parameterized Explanations for Investor / Company Matching

Matching companies and investors is usually considered a highly speciali...

0 Simerjot Kaur, et al. ∙

research

∙ 10/05/2021

Tradeoffs in Streaming Binary Classification under Limited Inspection Resources

Institutions are increasingly relying on machine learning models to iden...

5 Parisa Hassanzadeh, et al. ∙

research

∙ 07/02/2021

Visual Time Series Forecasting: An Image-driven Approach

In this work, we address time-series forecasting as a computer vision ta...

0 Naftali Cohen, et al. ∙

research

∙ 05/21/2021

Waiting Tables as a Robot Planning Problem

We present how we formalize the waiting tables task in a restaurant as a...

0 Anahita Mohseni-Kabir, et al. ∙

research

∙ 05/09/2021

Advising Agent for Service-Providing Live-Chat Operators

Call centers, in which human operators attend clients using textual chat...

2 Aviram Aviv, et al. ∙

research

∙ 02/25/2021

Iterative Bounding MDPs: Learning Interpretable Policies via Non-Interpretable Methods

Current work in explainable reinforcement learning generally produces po...

7 Nicholay Topin, et al. ∙

research

∙ 02/25/2021

Theory and Analysis of Optimal Planning over Long and Infinite Horizons for Achieving Independent Partially-Observable Tasks that Evolve over Time

We present the theoretical analysis and proofs of a recently developed a...

0 Anahita Mohseni-Kabir, et al. ∙

research

∙ 02/24/2021

Deep Video Prediction for Time Series Forecasting

Time series forecasting is essential for decision making in many domains...

14 Zhen Zeng, et al. ∙

research

∙ 01/06/2021

Playing with Food: Learning Food Item Representations through Interactive Exploration

A key challenge in robotic food manipulation is modeling the material pr...

0 Amrita Sawhney, et al. ∙

research

∙ 11/18/2020

Visual Forecasting of Time Series with Image-to-Image Regression

Time series forecasting is essential for agents to make decisions in man...

26 Naftali Cohen, et al. ∙

research

∙ 11/03/2020

Domain-independent generation and classification of behavior traces

Financial institutions mostly deal with people. Therefore, characterizin...

3 Daniel Borrajo, et al. ∙

research

∙ 11/03/2020

Simulating and classifying behavior in adversarial environments based on action-state traces: an application to money laundering

Many business applications involve adversarial relationships in which bo...

6 Daniel Borrajo, et al. ∙

research

∙ 10/23/2020

Robust Document Representations using Latent Topics and Metadata

Task specific fine-tuning of a pre-trained neural language model using a...

2 Natraj Raman, et al. ∙

research

∙ 10/12/2020

SURF: Improving classifiers in production by learning from busy and noisy end users

Supervised learning classifiers inevitably make mistakes in production, ...

0 Joshua Lockhart, et al. ∙

research

∙ 10/09/2020

Paying down metadata debt: learning the representation of concepts using topic models

We introduce a data management problem called metadata debt, to identify...

0 Jiahao Chen, et al. ∙

research

∙ 10/02/2020

AI pptX: Robust Continuous Learning for Document Generation with AI Insights

Business analysts create billions of slide decks, reports and documents ...

0 Vineeth Ravi, et al. ∙

research

∙ 06/23/2020

Calibration of Shared Equilibria in General Sum Partially Observable Markov Games

Training multi-agent systems (MAS) to achieve realistic equilibria gives...

0 Nelson Vadori, et al. ∙

research

∙ 06/23/2020

Risk-Sensitive Reinforcement Learning: a Martingale Approach to Reward Uncertainty

We introduce a novel framework to account for sensitivity to rewards unc...

0 Nelson Vadori, et al. ∙

research

∙ 05/12/2020

Guaranteeing Reproducibility in Deep Learning Competitions

To encourage the development of methods with reproducible and robust tra...

3 Brandon Houghton, et al. ∙

research

∙ 04/27/2020

Some people aren't worth listening to: periodically retraining classifiers with feedback from a team of end users

Document classification is ubiquitous in a business setting, but often t...

13 Joshua Lockhart, et al. ∙

research

∙ 04/14/2020

Latent Bayesian Inference for Robust Earnings Estimates

Equity research analysts at financial institutions play a pivotal role i...

6 Chirag Nagpal, et al. ∙

research

∙ 04/09/2020

Heuristics for Link Prediction in Multiplex Networks

Link prediction, or the inference of future or missing connections betwe...

7 Robert E. Tillman, et al. ∙

research

∙ 12/10/2019

Get Real: Realism Metrics for Robust Limit Order Book Market Simulations

Machine learning (especially reinforcement learning) methods for trading...

0 Svitlana Vyetrenko, et al. ∙

research

∙ 11/28/2019

Playing Games in the Dark: An approach for cross-modality transfer in reinforcement learning

In this work we explore the use of latent representations obtained from ...

8 Rui Silva, et al. ∙

research

∙ 11/14/2019

Reinforcement Learning for Market Making in a Multi-agent Dealer Market

Market makers play an important role in providing liquidity to markets b...

0 Sumitra Ganesh, et al. ∙

research

∙ 10/24/2019

A Robot's Expressive Language Affects Human Strategy and Perceptions in a Competitive Game

As robots are increasingly endowed with social and communicative capabil...

0 Aaron M. Roth, et al. ∙

research

∙ 09/27/2019

Leveraging Multimodal Haptic Sensory Data for Robust Cutting

Cutting is a common form of manipulation when working with divisible obj...

0 Kevin Zhang, et al. ∙

research

∙ 07/29/2019

MineRL: A Large-Scale Dataset of Minecraft Demonstrations

The sample inefficiency of standard deep reinforcement learning methods ...

7 William H. Guss, et al. ∙

research

∙ 07/23/2019

Trading via Image Classification

The art of systematic financial trading evolved with an array of approac...

4 Naftali Cohen, et al. ∙

research

∙ 07/22/2019

The Effect of Visual Design in Image Classification

Financial companies continuously analyze the state of the markets to ret...

7 Naftali Cohen, et al. ∙

research

∙ 07/02/2019

Conservative Q-Improvement: Reinforcement Learning for an Interpretable Decision-Tree Policy

There is a growing desire in the field of reinforcement learning (and ma...

2 Aaron M. Roth, et al. ∙

research

∙ 05/28/2019

Generation of Policy-Level Explanations for Reinforcement Learning

Though reinforcement learning has greatly benefited from the incorporati...

0 Nicholay Topin, et al. ∙

research

∙ 04/22/2019

The MineRL Competition on Sample Efficient Reinforcement Learning using Human Priors

Though deep reinforcement learning has led to breakthroughs in many diff...

10 William H. Guss, et al. ∙

research

∙ 12/18/2018

Proceedings of the Workshop on Social Robots in Therapy: Focusing on Autonomy and Ethical Challenges

Robot-Assisted Therapy (RAT) has successfully been used in HRI research ...

0 Pablo G. Esteban, et al. ∙

Manuela Veloso

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