Manuela Veloso

research

∙ 07/27/2022

Differentially Private Learning of Hawkes Processes

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

Mohsen Ghassemi, et al. ∙

research

∙ 02/17/2022

A Survey of Explainable Reinforcement Learning

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

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...

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...

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...

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...

Selim Amrouni, et al. ∙

research

∙ 10/27/2021

Parameterized Explanations for Investor / Company Matching

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

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...

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...

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...

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...

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...

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...

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...

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...

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...

Naftali Cohen, et al. ∙

research

∙ 11/03/2020

Domain-independent generation and classification of behavior traces

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

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...

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...

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, ...

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...

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 ...

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...

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...

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...

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...

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...

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...

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...

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 ...

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...

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...

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...

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 ...

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...

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...

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...

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...

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...

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 ...

Pablo G. Esteban, et al. ∙

research

∙ 06/10/2018

The Impact of Humanoid Affect Expression on Human Behavior in a Game-Theoretic Setting

With the rapid development of robot and other intelligent and autonomous...

Aaron M. Roth, et al. ∙

research

∙ 02/11/2018

Understanding Convolutional Networks with APPLE : Automatic Patch Pattern Labeling for Explanation

With the success of deep learning, recent efforts have been focused on a...

Sandeep Konam, et al. ∙

research

∙ 12/15/2017

What Can This Robot Do? Learning from Appearance and Experiments

When presented with an unknown robot (subject) how can an autonomous age...

Ashwin Khadke, et al. ∙

research

∙ 09/26/2017

UAV and Service Robot Coordination for Indoor Object Search Tasks

Our CoBot robots have successfully performed a variety of service tasks ...

Sandeep Konam, et al. ∙

research

∙ 07/30/2017

Towards Visual Explanations for Convolutional Neural Networks via Input Resampling

The predictive power of neural networks often costs model interpretabili...

Benjamin J. Lengerich, et al. ∙

research

∙ 05/30/2017

Learning End-to-end Multimodal Sensor Policies for Autonomous Navigation

Multisensory polices are known to enhance both state estimation and targ...

Guan-Horng Liu, et al. ∙

research

∙ 01/15/2014

Interactive Policy Learning through Confidence-Based Autonomy

We present Confidence-Based Autonomy (CBA), an interactive algorithm for...

Sonia Chernova, et al. ∙

Manuela Veloso

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