Amazon Research Awards

Award Recipients

  • Arash Ajoudani

    Effective, Ergonomic, and Lean Logistics through Reconfigurable and Mobile Collaborative Robots
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  • Javier Alonso-Mora

    Predictive Multi-objective Fleet Routing and Assignment
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  • Chris Amato

    Optimizing Communication and Throughput of Teams of Robots under Uncertainty
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  • Sven Behnke

    Generalizing Scene Parsing for Cluttered Bin Picking
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  • Taylor Berg-Kirkpatrick

    Unsupervised Discovery of Linguistic Structure using Invertible Neural Projections
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  • Arnab Bhattacharyya

    Efficient Inference and Testing of High-Dimensional Causal Models
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  • Joydeep Biswas

    The Joint Perception Formulation For Long-Term Autonomy
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  • Jeannette Bohg

    Multimodal Object Representations for Truly Immersive Virtual Reality
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  • Byron Boots

    Learning Safe, Stable, and Interpretable Motion Policies from Data
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  • Soumen Chakrabarti

    Neural Decomposition of Complex Queries Into Subqueries Over Knowledge Graph and Corpus
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  • Philip Chan

    Open Set Recognition in Malware Classification via Learning Latent Representation of Function Call Graphs
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  • Moses Charikar

    Efficient Algorithms for High-Dimensional Statistics
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  • Matei Ciocarlie

    Sample-efficient Motor Learning for Tactile Grasping in Clutter
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  • Trevor Cohn

    Semi-supervised Stochastic Domain Adaptation
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  • Peter Corke

    From reactive grasping to grasping with intent
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  • Jose Correa

    Posted Price Mechanisms
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  • Shane Culpepper

    Efficient and Effective Cascaded Ranking for Large Scale Search
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  • Philip Dames

    Safe Navigation Through Crowded Dynamic Environments
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  • Emiliano De Cristofaro

    Studying and Mitigating Inference Attacks on Collaborative Federated Learning
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  • Dean Eckles

    Complex modeling and inference with online rating data
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  • Michal Feldman

    Algorithmic Mechanism Design: Beyond Independent Private Preferences
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  • Lise Getoor

    A Probabilistic Approach for Entity Resolution, Variation Discovery and Product Graph Construction
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  • Kevin Gimpel

    Structured Prediction Energy Networks for Neural Machine Translation
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  • Vineet Goyal

    Assortment Planning for Fashion Products
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  • Grace Gu

    Pneumatically actuated robotic joints: Design, 4D-printing, and experiment
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  • Gholamreza Haffari

    Effective Multi-Task Learning for Neural Machine Translation
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  • Daniel Harabor

    Symmetry Breaking Constraints for Multi-agent Pathfinding
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  • Bharath Hariharan

    Recognizing fine-grained fashion elements across domains
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  • Kris Hauser

    Closed-Loop Robotic Packing for Irregular and Diverse Objects
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  • Otmar Hilliges

    Unsupervised 3D Hand Pose Estimation from Monocular RGB
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  • Bert Huang

    Measuring and Mitigating Intersectional Unfairness of Recommendation
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  • Kevin Jamieson

    Robust Pure-Exploration with Environmental Context
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  • Longin Jan Latecki

    Focus Area Image Search with Target Object Detection
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  • Kinshuk Jerath

    Advertisements on Online Marketplaces
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  • Amin Karbasi

    Leveraging Combinatorial Structures for Scalable Learning
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  • Samir Khuller

    Data Movement and Scheduling in Data Centers
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  • Ross Knepper

    Learning High-level Robot Behaviors by Predicting State Visitation Distributions
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  • Sven Koenig

    Hierarchical MAPF Planning for Warehouse Solutions
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  • Danai Koutra

    Adaptive Personalized Knowledge Graph Summarization
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  • Adriana Kovashka

    Functional objects: How objects foreshadow film plots and explain advertisements
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  • Ales Leonardis

    Understanding complex scenes in contained spaces using physics and generative deep learning
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  • Fuxin Li

    Deep Mumford-Shah Instance Segmentation with Orientational Distances
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  • Bo Liu

    Sequential Transaction Risk Management with Deep Reinforcement Learning
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  • Haiping Lu

    Learning Representations of Higher-Order Structures for Networks via Tensor Embedding
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  • Anirudha Majumdar

    Grasping Novel Objects with Provable Guarantees via Generalization Theory
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  • Raymond Mooney

    Language-Aided Learning from Demonstration
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  • Francesc Moreno-Noguer

    Geometry-aware 3D Human Body Animation from Still Photos
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  • Nick Nikiforakis

    ICBots: Tools and Techniques for Detecting Web Bots
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  • Olga Papaemmanouil

    Query Performance Modeling via Deep Learning
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  • Barbara Plank

    Multi-Task Sequence Labeling Under Adverse Conditions
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  • Robert Platt

    Using symbolic planning to guide sensorimotor learning for robotic manipulation
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  • Hayder Radha

    Joint Multi-Target Tracking and Classification for Fully Autonomous Robots Operating within Dynamic Warehouse Environments
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  • Xiang Ren

    Model Programming: Model-Level Fusion of Structured Knowledge Priors for Information Extraction
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  • Alan Ritter

    Integrating Data-Driven Conversation in Open-Domain Question Answering
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  • Aaron Roth

    Practical, Meaningful Fairness Guarantees in Machine Learning
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  • Guy Rothblum

    Composition of Local Differential Privacy At Scale
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  • Daniela Rus

    Integrated Data-Driven Perception and Model-based Planning for Robots and Applications to Robot Manipulation
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  • Amin Saberi

    Advertising on Amazon, an algorithmic perspective
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  • Dorsa Sadigh

    Active Learning of Teleoperation Maps
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  • Chirag Shah

    Addressing Cold Start Problem in Personalization and Recommendation Using Proactive Information Retrieval
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  • Dafna Shahaf

    Playful Conversational AI
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  • Roland Siegwart

    Multi-modal Perception for Object-based Mapping and Localization
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  • Aravind Srinivasan

    Algorithms for Cloud-Service and Ad-Delivery Optimization
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  • Erik Strumbelj

    Scalable fully-Bayesian inference in Stan
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  • Gaurav Sukhatme

    Watch, Practice, Learn, Do: Unsupervised Learning of Robust and Composable Robot Motion Skills by Fusing Expert Demonstrations with Robot Experience
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  • Yizhou Sun

    On Knowledge Quality Enhancement via Path-Guided Logic-Based Uncertain Knowledge Graph Embedding
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  • Hari Sundaram

    Towards Robust and Scalable Neural Recommendations in the Presence of Temporal Sparsity and User Preference Skew
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  • Eva Tardos

    Economic Inference and Algorithmic Learning in Games
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  • Russ Tedrake

    Feedback Control for Dexterous Manipulation
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  • Yuan Tian

    Dynamic Graph-based Anomaly Detection for Cloud Computing
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  • James Tompkin

    Learning Real-time View Synthesis for Robot Virtual Reality Teleoperation
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  • Philip Torr

    Incremental Learning in Extremely Deep Networks
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  • Richard Turner

    Continual deep learning via meta-learning and probabilistic inference
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  • Gregory Valiant

    Estimating Learnability
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  • Joaquin Vanschoren

    The AutoML Gym
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  • Greg Ver Steeg

    Information-theoretic Invariant Representation Learning
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  • Carl Vondrick

    Anticipating Human Behaviors from Unlabeled Video
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  • He Wang

    Marketplace Design for Long-haul Ground Transportation
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  • James Wang

    An Open Emotion Understanding Dataset
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  • Andrew Wilson

    New Directions for Non-Convex Optimization in Deep Learning
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  • Bin Yu

    Interpretable machine-learning for extracting dataset-level interactions
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  • Georgia Zellou

    Applying human “speech rules” to Alexa: Impact of acoustic-phonetic modifications on device engagement and perceived naturalness
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  • Shipra Agrawal

    Columbia University
    New Algorithmic Approaches for Reinforcement learning, with Application to Integer Programming
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  • Avishek Anand

    Leibniz Universitat Hannover
    Interpretability of Neural Rankers
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  • Nina Balcan

    Carnegie Mellon University
    Differentially-Private Learning for Massive Data Problems: Theory and Applications
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  • David Bamman

    University of California, Berkeley
    Natural Language Processing for Literary Texts
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  • Matthew Blaschko

    KU Leuven
    Low resource, highly-scalable discrete deep networks for the Amazon Bin Image Dataset Challenge
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  • Tevfik Bultan

    University of California, Santa Barbara
    Automatically Detecting Bugs in Identity and Access Management Policies
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  • Yinzhi Cao

    Lehigh University
    Cross-browser Fingerprinting: Attacks, Dynamics, and Detection
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  • Jia Deng

    University of Michigan
    Holistic Parsing of Human Activities in Videos
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  • Kevin Duh

    Johns Hopkins University
    Multi-objective Hyperparameter Search for Fast and Accurate Neural Machine Translation
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  • Jason Eisner

    Johns Hopkins University
    Continuous-Time Reinforcement Learning For Personalization
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  • Ron Fedkiw

    Stanford University
    Representation Learning for Cloth
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  • Maria Gini

    University of Minnesota
    Multi-robot Allocation and Scheduling of Tasks with Temporal Constraints
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  • Kristen Grauman

    University of Texas at Austin
    Explainable Visual Compatibility and Style Forecasting with Fashion Images
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  • Hannaneh Hajishirzi

    University of Washington
    Question Answering and Reasoning about Product Reviews
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  • Max Harper

    University of Minnesota
    Building Blocks for Natural Language Recommenders
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  • Kris Hauser

    Duke University
    Optimized Robotic Packing for Irregular and Diverse Objects
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  • Ralph Hollis

    Carnegie Mellon University
    Conversational Mobile Robots in Human Environments
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  • Piotr Indyk

    Massachusetts Institute of Technology
    Towards Accurate, Robust and Dynamic Metric Compression
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  • Thorsten Joachims

    Cornell University
    Unbiased Learning with Biased User Feedback
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  • Ross Knepper

    Cornell University
    Transferring Deep Reinforcement Learning Policies from Simulation to Real World for Robotic Manipulation of Soft Bodies
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  • Sven Koenig

    University of Southern California
    Multi-Agent Path Finding for Fulfillment Centers
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  • Oliver Kroemer

    Carnegie Mellon University
    Learning Recovery Skills for Robust Grasping and Manipulation
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  • Ranjitha Kumar

    University of Illinois at Urbana-Champaign
    An Experimentation Engine for Personal Fashion
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  • Svetlana Lazebnik

    University of Illinois at Urbana-Champaign
    Compositional Image Captioning Using High-Level Cues
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  • Chin-Hui Lee

    Georgia Institute of Technology
    Integrating Signal Pre-processing and Model Post-processing for Robust Single- and Multi-Channel Speech Recognition
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  • Jure Leskovec

    Stanford University
    MATLearn: Deep Representation Learning for Complex Malicious Behavior Detection
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  • Sergey Levine

    University of California, Berkeley
    Deep Reinforcement Learning for Dexterous Manipulation from Vision and Touch
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  • Percy Liang

    Stanford University
    Learning to Understand Natural Language Commands on Changing Websites
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  • Christopher Manning

    Stanford University
    Enabling Multilingual Language Understanding: Universal Typed Semantic Parsing
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  • Florian Metze

    Carnegie Mellon University
    Speech- and Image-to-Text for Video Captioning
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  • Sriraam Natarajan

    University of Texas at Dallas
    Guiding Probabilistic Learning in Structured Domains with Crowd-Sourced Inputs: Treating Humans as More Than Mere Labelers
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  • Ramakant Nevatia

    University of Southern California
    Open-vocabulary Activity Detection and Localization in Videos
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  • Robert Platt

    Northeastern University
    Better Robotic Manipulation via Deep Deictic Reinforcement Learning
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  • Theodoros Rekatsinas

    University of Wisconsin - Madison
    Statistical Learning and Probabilistic Inference Methods for Interactive Data Cleaning
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  • Alberto Rodriguez

    Massachusetts Institute of Technology
    Reactive Grasping with Tactile Reflexes
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  • Daniela Rus

    Massachusetts Institute of Technology
    Soft Hands for Packing and Unpacking
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  • Sebastian Scherer

    Carnegie Mellon University
    Multi-view 3D Object Detection and SLAM
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  • Cordelia Schmid

    Inria
    3D Understanding of Humans in Action from Real-World Videos
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  • Anshumali Shrivastava

    Rice University
    Scaling-up Machine Learning via Probabilistic Hashing
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  • Justin Solomon

    Massachusetts Institute of Technology
    Large-Scale Geometrically-Structured Sampling
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  • Suvrit Sra

    Massachusetts Institute of Technology
    Variable precision scalable nonconvex optimization
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  • Siddartha Srinivasa

    University of Washington
    Learning to Close the Gap between Simulators and Reality for Robotic Manipulation under Clutter and Uncertainty
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  • Torsten Suel

    New York University
    Exploring Index Tiering Methods for General and E-Commerce Search
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  • Charles Sutton

    University of Edinburgh
    DeepClean: Deep Learning for Inferring Data Cleaning Scripts
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  • Russ Tedrake

    Massachusetts Institute of Technology
    Robust Multi-Modal Perception for Manipulation in Clutter
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  • Frederico Tombari

    TU Munich
    Fully-monocular dense semantic SLAM for persistent and long-scene understanding
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  • Olga Vechtomova

    University of Waterloo
    Task-based latent semantic information retrieval
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  • Eugene Wu

    Columbia University
    Interactive Matcher Debugging via Adversarial Generation
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  • Luke Zettemoyer

    University of Washington
    Cross Sentence QA-SRL: Data and Algorithms for Recovering Implicit Semantic Relationships in Text
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  • Dhruv Batra

    Georgia Tech, USA
    Visual Dialog
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  • Matthew Blaschko

    University of Leuven, Belgium
    Co-regularization and Deep, Weakly-Supervised Segmentation of the Amazon Bin Image Data Set
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  • David Chiang

    University of Notre Dame, USA
    New Directions for Whole-Sentence Training of Neural Translation Models
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  • Hal Daume

    Univerity of Maryland, US
    Neural Machine Translation from Weak User Feedback
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  • Desmond Elliott

    University of Amsterdam, Holland
    Effective Approaches to Multitask Multimodal Translation
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  • Sanja Fidler

    University of Toronto, Canada
    Towards Natural Online Clothing Retail
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  • Kristen Grauman

    University of Texas, US
    Visual Style and Subtleties: Attributes for Search and Recommendation in Fashion Images
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  • Marcin Junczys-Dowmunt

    University of Edinburgh, UK
    Deployment-ready Open-source Neural Machine Translation
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  • Bastian Leibe

    RWTH Aachen, Germany
    End-to-End Deep Learning for Human Pose Estimation in Video
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  • Adam Lopez

    University of Edinburgh, UK
    Machine Translation on GPUs
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  • Graham Neubig

    Carnegie Mellon University, US
    Unified Neural Models of Morphological Analysis and Generation
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  • Devi Parikh

    Georgia Tech, USA
    Counting Everyday Objects in Everyday Scenes
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  • Maryam Rahnemoonfar

    Texas A&M University-Corpus Christi, USA
    RT - HPC: Real Time Heterogeneous Product Counting on Amazon Bin Image Dataset based on Deep Learning
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  • Cordelia Schmid

    Inria, France
    3D Human Action Recognition from Monocular RGB Videos
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  • Lucia Specia

    University of Sheffield, UK
    Predicting Relevance and Quality of Machine Translation for Product Reviews
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  • Graham Taylor

    University of Guelph, Canada
    Parametrizing input to a deep learning architecture
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  • Antonio Torralba

    Massachusetts Institute of Technology, USA
    Learning vision and language by watching movies and reading books
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  • Raquel Urtasun

    University of Toronto, Canada
    Holistic Deep Scene Parsing of Amazon Fulfillment Centers
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  • Chris Callison-Burch

    University of Pennsylvania, USA
    Low Resource Machine Translation via Matrix Factorization
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  • Marine Carpuat

    University of Maryland, USA
    Modeling Divergence in Bilingual Sentence Pairs for Machine Translation
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  • Kenneth Heafield

    University of Edinburgh, UK
    Faster Decoding and Better Features via Local Coarse-to-Fine
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  • Philipp Koehn

    Johns Hopkins University, USA
    Efficient High-Speed Search for Phrase-Based Statistical Machine Translation
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  • Matt Post

    Johns Hopkins University, USA
    Translation into morphologically rich languages with source-side annotations
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  • Stefan Riezler

    Heidelberg University, Germany
    Multimodal Pivots for Low Resource Machine Translation in E-Commerce Localization
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  • Lane Schwartz

    University of Illinois at Urbana-Champaign, USA
    Simple and Reliable Workflow management for replicable scientific computing
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