University of Michigan

∙ Ann Arbor , United States ∙ 0 followers

The University of Michigan, often simply referred to as Michigan, is a public research university in Ann Arbor, Michigan.

Towards Automatic Detection of Misinformation in Online Medical Videos

Recent years have witnessed a significant increase in the online sharing...
09/04/2019 ∙ by Rui Hou, et al. ∙ 54 ∙ share

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Attacking Vision-based Perception in End-to-End Autonomous Driving Models

Recent advances in machine learning, especially techniques such as deep ...
10/02/2019 ∙ by Adith Boloor, et al. ∙ 35 ∙ share

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Emotion Recognition in Conversation: Research Challenges, Datasets, and Recent Advances

Emotion is intrinsic to humans and consequently emotion understanding is...
05/08/2019 ∙ by Soujanya Poria, et al. ∙ 32 ∙ share

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Deep Learning for Automatic Pneumonia Detection

Pneumonia is the leading cause of death among young children and one of ...
05/28/2020 ∙ by Tatiana Gabruseva, et al. ∙ 32 ∙ share

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AuxNet: Auxiliary tasks enhanced Semantic Segmentation for Automated Driving

Decision making in automated driving is highly specific to the environme...
01/17/2019 ∙ by Sumanth Chennupati, et al. ∙ 30 ∙ share

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What Can Learned Intrinsic Rewards Capture?

Reinforcement learning agents can include different components, such as ...
12/11/2019 ∙ by Zeyu Zheng, et al. ∙ 25 ∙ share

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Monocular Depth Prediction Through Continuous 3D Loss

This paper reports a new continuous 3D loss function for learning depth ...
03/21/2020 ∙ by Minghan Zhu, et al. ∙ 23 ∙ share

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Shadow Transfer: Single Image Relighting For Urban Road Scenes

Illumination effects in images, specifically cast shadows and shading, h...
09/23/2019 ∙ by Alexandra Carlson, et al. ∙ 22 ∙ share

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Unified Vision-Language Pre-Training for Image Captioning and VQA

This paper presents a unified Vision-Language Pre-training (VLP) model. ...
09/24/2019 ∙ by Luowei Zhou, et al. ∙ 17 ∙ share

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Near-optimal Oracle-efficient Algorithms for Stationary and Non-Stationary Stochastic Linear Bandits

We investigate the design of two algorithms that enjoy not only computat...
12/11/2019 ∙ by Baekjin Kim, et al. ∙ 17 ∙ share

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How Should an Agent Practice?

We present a method for learning intrinsic reward functions to drive the...
12/15/2019 ∙ by Janarthanan Rajendran, et al. ∙ 17 ∙ share

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Eliminating artefacts in Polarimetric Images using Deep Learning

Polarization measurements done using Imaging Polarimeters such as the Ro...
11/19/2019 ∙ by Dhruv Paranjpye, et al. ∙ 16 ∙ share

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Project and Forget: Solving Large-Scale Metric Constrained Problems

Given a set of dissimilarity measurements amongst data points, determini...
05/08/2020 ∙ by Rishi Sonthalia, et al. ∙ 16 ∙ share

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Scaling-up Distributed Processing of Data Streams for Machine Learning

Emerging applications of machine learning in numerous areas involve cont...
05/18/2020 ∙ by Matthew Nokleby, et al. ∙ 16 ∙ share

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VirTex: Learning Visual Representations from Textual Annotations

The de-facto approach to many vision tasks is to start from pretrained v...
06/11/2020 ∙ by Karan Desai, et al. ∙ 16 ∙ share

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Simple Physical Adversarial Examples against End-to-End Autonomous Driving Models

Recent advances in machine learning, especially techniques such as deep ...
03/12/2019 ∙ by Adith Boloor, et al. ∙ 14 ∙ share

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HCNAF: Hyper-Conditioned Neural Autoregressive Flow and its Application for Probabilistic Occupancy Map Forecasting

We introduce Hyper-Conditioned Neural Autoregressive Flow (HCNAF); a pow...
12/17/2019 ∙ by Jean-Sebastien Valois, et al. ∙ 14 ∙ share

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What is Normal, What is Strange, and What is Missing in a Knowledge Graph: Unified Characterization via Inductive Summarization

Knowledge graphs (KGs) store highly heterogeneous information about the ...
03/23/2020 ∙ by Caleb Belth, et al. ∙ 13 ∙ share

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Efficient Adversarial Training with Transferable Adversarial Examples

Adversarial training is an effective defense method to protect classific...
12/27/2019 ∙ by Haizhong Zheng, et al. ∙ 12 ∙ share

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On Learnability under General Stochastic Processes

Statistical learning theory under independent and identically distribute...
05/15/2020 ∙ by A. Philip Dawid, et al. ∙ 12 ∙ share

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Adversarial Sensor Attack on LiDAR-based Perception in Autonomous Driving

In Autonomous Vehicles (AVs), one fundamental pillar is perception, whic...
07/16/2019 ∙ by Yulong Cao, et al. ∙ 11 ∙ share

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BRPO: Batch Residual Policy Optimization

In batch reinforcement learning (RL), one often constrains a learned pol...
02/08/2020 ∙ by Sungryull Sohn, et al. ∙ 11 ∙ share

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Sparsity-promoting algorithms for the discovery of informative Koopman invariant subspaces

Koopman decomposition is a non-linear generalization of eigen decomposit...
02/25/2020 ∙ by Shaowu Pan, et al. ∙ 11 ∙ share

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Novel Object Viewpoint Estimation through Reconstruction Alignment

The goal of this paper is to estimate the viewpoint for a novel object. ...
06/05/2020 ∙ by Mohamed El Banani, et al. ∙ 11 ∙ share

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Rethinking Numerical Representations for Deep Neural Networks

With ever-increasing computational demand for deep learning, it is criti...
08/07/2018 ∙ by Parker Hill, et al. ∙ 10 ∙ share

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D3D: Distilled 3D Networks for Video Action Recognition

State-of-the-art methods for video action recognition commonly use an en...
12/19/2018 ∙ by Jonathan C. Stroud, et al. ∙ 10 ∙ share

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Face-to-Parameter Translation for Game Character Auto-Creation

Character customization system is an important component in Role-Playing...
09/03/2019 ∙ by Tianyang Shi, et al. ∙ 10 ∙ share

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On the Equivalence between Online and Private Learnability beyond Binary Classification

Alon et al. [2019] and Bun et al. [2020] recently showed that online lea...
06/02/2020 ∙ by Young Hun Jung, et al. ∙ 10 ∙ share

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Tree! I am no Tree! I am a Low Dimensional Hyperbolic Embedding

Given data, finding a faithful low-dimensional hyperbolic embedding of t...
05/08/2020 ∙ by Rishi Sonthalia, et al. ∙ 9 ∙ share

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Understanding Human Hands in Contact at Internet Scale

Hands are the central means by which humans manipulate their world and b...
06/11/2020 ∙ by Dandan Shan, et al. ∙ 9 ∙ share

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Improving Text-to-SQL Evaluation Methodology

To be informative, an evaluation must measure how well systems generaliz...
06/23/2018 ∙ by Catherine Finegan-Dollak, et al. ∙ 8 ∙ share

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Grounded Video Description

Video description is one of the most challenging problems in vision and ...
12/17/2018 ∙ by Luowei Zhou, et al. ∙ 8 ∙ share

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Which Factorization Machine Modeling is Better: A Theoretical Answer with Optimal Guarantee

Factorization machine (FM) is a popular machine learning model to captur...
01/30/2019 ∙ by Ming Lin, et al. ∙ 8 ∙ share

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Personalized HeartSteps: A Reinforcement Learning Algorithm for Optimizing Physical Activity

With the recent evolution of mobile health technologies, health scientis...
09/08/2019 ∙ by Peng Liao, et al. ∙ 7 ∙ share

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Discovery of Useful Questions as Auxiliary Tasks

Arguably, intelligent agents ought to be able to discover their own ques...
09/10/2019 ∙ by Vivek Veeriah, et al. ∙ 7 ∙ share

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DispSegNet: Leveraging Semantics for End-to-End Learning of Disparity Estimation from Stereo Imagery

Recent work has shown that convolutional neural networks (CNNs) can be a...
09/13/2018 ∙ by Junming Zhang, et al. ∙ 6 ∙ share

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Learning Constraints from Demonstrations

We extend the learning from demonstration paradigm by providing a method...
12/17/2018 ∙ by Glen Chou, et al. ∙ 6 ∙ share

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Contextual Markov Decision Processes using Generalized Linear Models

We consider the recently proposed reinforcement learning (RL) framework ...
03/14/2019 ∙ by Aditya Modi, et al. ∙ 6 ∙ share

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The Ambiguous World of Emotion Representation

Artificial intelligence and machine learning systems have demonstrated h...
09/01/2019 ∙ by Vidhyasaharan Sethu, et al. ∙ 6 ∙ share

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Thompson Sampling in Non-Episodic Restless Bandits

Restless bandit problems assume time-varying reward distributions of the...
10/12/2019 ∙ by Young Hun Jung, et al. ∙ 6 ∙ share

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Compositional Temporal Visual Grounding of Natural Language Event Descriptions

Temporal grounding entails establishing a correspondence between natural...
12/04/2019 ∙ by Jonathan C. Stroud, et al. ∙ 6 ∙ share

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Generalizing Graph Neural Networks Beyond Homophily

We investigate the representation power of graph neural networks in the ...
06/20/2020 ∙ by Jiong Zhu, et al. ∙ 6 ∙ share

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GluonCV and GluonNLP: Deep Learning in Computer Vision and Natural Language Processing

We present GluonCV and GluonNLP, the deep learning toolkits for computer...
07/09/2019 ∙ by Jian Guo, et al. ∙ 5 ∙ share

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Variational Fusion for Multimodal Sentiment Analysis

Multimodal fusion is considered a key step in multimodal tasks such as s...
08/13/2019 ∙ by Navonil Majumder, et al. ∙ 5 ∙ share

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TASED-Net: Temporally-Aggregating Spatial Encoder-Decoder Network for Video Saliency Detection

TASED-Net is a 3D fully-convolutional network architecture for video sal...
08/15/2019 ∙ by Kyle Min, et al. ∙ 5 ∙ share

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Semantically-Guided Representation Learning for Self-Supervised Monocular Depth

Self-supervised learning is showing great promise for monocular depth es...
02/27/2020 ∙ by Vitor Guizilini, et al. ∙ 5 ∙ share

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Improving the Utility of Knowledge Graph Embeddings with Calibration

This paper addresses machine learning models that embed knowledge graph ...
04/02/2020 ∙ by Tara Safavi, et al. ∙ 5 ∙ share

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ShapeAdv: Generating Shape-Aware Adversarial 3D Point Clouds

We introduce ShapeAdv, a novel framework to study shape-aware adversaria...
05/24/2020 ∙ by Kibok Lee, et al. ∙ 5 ∙ share

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Neural Execution Engines: Learning to Execute Subroutines

A significant effort has been made to train neural networks that replica...
06/15/2020 ∙ by Yujun Yan, et al. ∙ 5 ∙ share

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Pull Message Passing for Nonparametric Belief Propagation

We present a "pull" approach to approximate products of Gaussian mixture...
07/27/2018 ∙ by Karthik Desingh, et al. ∙ 4 ∙ share

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