Manuela Veloso

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J.P. Morgan ∙ Carnegie Mellon University

Herbert A. Simon University Professor, Head, Machine Learning Department at Carnegie Mellon University

Visual Time Series Forecasting: An Image-driven Approach

In this work, we address time-series forecasting as a computer vision ta...
07/02/2021 ∙ by Naftali Cohen, et al. ∙ 0 ∙ share

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Waiting Tables as a Robot Planning Problem

We present how we formalize the waiting tables task in a restaurant as a...
05/21/2021 ∙ by Anahita Mohseni-Kabir, et al. ∙ 0 ∙ share

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Advising Agent for Service-Providing Live-Chat Operators

Call centers, in which human operators attend clients using textual chat...
05/09/2021 ∙ by Aviram Aviv, et al. ∙ 2 ∙ share

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

Current work in explainable reinforcement learning generally produces po...
02/25/2021 ∙ by Nicholay Topin, et al. ∙ 7 ∙ share

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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...
02/25/2021 ∙ by Anahita Mohseni-Kabir, et al. ∙ 0 ∙ share

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Deep Video Prediction for Time Series Forecasting

Time series forecasting is essential for decision making in many domains...
02/24/2021 ∙ by Zhen Zeng, et al. ∙ 14 ∙ share

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Playing with Food: Learning Food Item Representations through Interactive Exploration

A key challenge in robotic food manipulation is modeling the material pr...
01/06/2021 ∙ by Amrita Sawhney, et al. ∙ 0 ∙ share

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

Time series forecasting is essential for agents to make decisions in man...
11/18/2020 ∙ by Naftali Cohen, et al. ∙ 26 ∙ share

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Domain-independent generation and classification of behavior traces

Financial institutions mostly deal with people. Therefore, characterizin...
11/03/2020 ∙ by Daniel Borrajo, et al. ∙ 3 ∙ share

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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...
11/03/2020 ∙ by Daniel Borrajo, et al. ∙ 6 ∙ share

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Robust Document Representations using Latent Topics and Metadata

Task specific fine-tuning of a pre-trained neural language model using a...
10/23/2020 ∙ by Natraj Raman, et al. ∙ 2 ∙ share

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

Supervised learning classifiers inevitably make mistakes in production, ...
10/12/2020 ∙ by Joshua Lockhart, et al. ∙ 0 ∙ share

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

We introduce a data management problem called metadata debt, to identify...
10/09/2020 ∙ by Jiahao Chen, et al. ∙ 0 ∙ share

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

Business analysts create billions of slide decks, reports and documents ...
10/02/2020 ∙ by Vineeth Ravi, et al. ∙ 0 ∙ share

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Calibration of Shared Equilibria in General Sum Partially Observable Markov Games

Training multi-agent systems (MAS) to achieve realistic equilibria gives...
06/23/2020 ∙ by Nelson Vadori, et al. ∙ 0 ∙ share

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

We introduce a novel framework to account for sensitivity to rewards unc...
06/23/2020 ∙ by Nelson Vadori, et al. ∙ 0 ∙ share

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Guaranteeing Reproducibility in Deep Learning Competitions

To encourage the development of methods with reproducible and robust tra...
05/12/2020 ∙ by Brandon Houghton, et al. ∙ 3 ∙ share

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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...
04/27/2020 ∙ by Joshua Lockhart, et al. ∙ 13 ∙ share

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Latent Bayesian Inference for Robust Earnings Estimates

Equity research analysts at financial institutions play a pivotal role i...
04/14/2020 ∙ by Chirag Nagpal, et al. ∙ 6 ∙ share

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Heuristics for Link Prediction in Multiplex Networks

Link prediction, or the inference of future or missing connections betwe...
04/09/2020 ∙ by Robert E. Tillman, et al. ∙ 7 ∙ share

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

Machine learning (especially reinforcement learning) methods for trading...
12/10/2019 ∙ by Svitlana Vyetrenko, et al. ∙ 0 ∙ share

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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 ...
11/28/2019 ∙ by Rui Silva, et al. ∙ 8 ∙ share

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

Market makers play an important role in providing liquidity to markets b...
11/14/2019 ∙ by Sumitra Ganesh, et al. ∙ 0 ∙ share

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

As robots are increasingly endowed with social and communicative capabil...
10/24/2019 ∙ by Aaron M. Roth, et al. ∙ 0 ∙ share

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Leveraging Multimodal Haptic Sensory Data for Robust Cutting

Cutting is a common form of manipulation when working with divisible obj...
09/27/2019 ∙ by Kevin Zhang, et al. ∙ 0 ∙ share

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MineRL: A Large-Scale Dataset of Minecraft Demonstrations

The sample inefficiency of standard deep reinforcement learning methods ...
07/29/2019 ∙ by William H. Guss, et al. ∙ 7 ∙ share

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Trading via Image Classification

The art of systematic financial trading evolved with an array of approac...
07/23/2019 ∙ by Naftali Cohen, et al. ∙ 4 ∙ share

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The Effect of Visual Design in Image Classification

Financial companies continuously analyze the state of the markets to ret...
07/22/2019 ∙ by Naftali Cohen, et al. ∙ 7 ∙ share

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

There is a growing desire in the field of reinforcement learning (and ma...
07/02/2019 ∙ by Aaron M. Roth, et al. ∙ 2 ∙ share

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Generation of Policy-Level Explanations for Reinforcement Learning

Though reinforcement learning has greatly benefited from the incorporati...
05/28/2019 ∙ by Nicholay Topin, et al. ∙ 0 ∙ share

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The MineRL Competition on Sample Efficient Reinforcement Learning using Human Priors

Though deep reinforcement learning has led to breakthroughs in many diff...
04/22/2019 ∙ by William H. Guss, et al. ∙ 10 ∙ share

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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 ...
12/18/2018 ∙ by Pablo G. Esteban, et al. ∙ 0 ∙ share

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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...
06/10/2018 ∙ by Aaron M. Roth, et al. ∙ 0 ∙ share

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

With the success of deep learning, recent efforts have been focused on a...
02/11/2018 ∙ by Sandeep Konam, et al. ∙ 0 ∙ share

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What Can This Robot Do? Learning from Appearance and Experiments

When presented with an unknown robot (subject) how can an autonomous age...
12/15/2017 ∙ by Ashwin Khadke, et al. ∙ 0 ∙ share

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UAV and Service Robot Coordination for Indoor Object Search Tasks

Our CoBot robots have successfully performed a variety of service tasks ...
09/26/2017 ∙ by Sandeep Konam, et al. ∙ 0 ∙ share

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Towards Visual Explanations for Convolutional Neural Networks via Input Resampling

The predictive power of neural networks often costs model interpretabili...
07/30/2017 ∙ by Benjamin J. Lengerich, et al. ∙ 0 ∙ share

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

Multisensory polices are known to enhance both state estimation and targ...
05/30/2017 ∙ by Guan-Horng Liu, et al. ∙ 0 ∙ share

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Interactive Policy Learning through Confidence-Based Autonomy

We present Confidence-Based Autonomy (CBA), an interactive algorithm for...
01/15/2014 ∙ by Sonia Chernova, et al. ∙ 0 ∙ share

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Manuela Veloso

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