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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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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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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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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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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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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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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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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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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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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Attribute-Guided Sketch Generation

Facial attributes are important since they provide a detailed descriptio...
01/28/2019 ∙ by Hao Tang, et al. ∙ 4 ∙ share

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Generalization Bounds in the Predict-then-Optimize Framework

The predict-then-optimize framework is fundamental in many practical set...
05/27/2019 ∙ by Othman El Balghiti, et al. ∙ 4 ∙ share

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Towards Multimodal Sarcasm Detection (An _Obviously_ Perfect Paper)

Sarcasm is often expressed through several verbal and non-verbal cues, e...
06/05/2019 ∙ by Santiago Castro, et al. ∙ 4 ∙ share

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Characterizing Attacks on Deep Reinforcement Learning

Deep reinforcement learning (DRL) has achieved great success in various ...
07/21/2019 ∙ by Chaowei Xiao, et al. ∙ 4 ∙ share

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No Press Diplomacy: Modeling Multi-Agent Gameplay

Diplomacy is a seven-player non-stochastic, non-cooperative game, where ...
09/04/2019 ∙ by Philip Paquette, et al. ∙ 4 ∙ share

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Mcity Data Collection for Automated Vehicles Study

The main goal of this paper is to introduce the data collection effort a...
12/12/2019 ∙ by Yiqun Dong, et al. ∙ 4 ∙ share

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Learning to Generate Synthetic 3D Training Data through Hybrid Gradient

Synthetic images rendered by graphics engines are a promising source for...
06/29/2019 ∙ by Dawei Yang, et al. ∙ 3 ∙ share

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Inferring Occluded Geometry Improves Performance when Retrieving an Object from Dense Clutter

Object search -- the problem of finding a target object in a cluttered s...
07/20/2019 ∙ by Andrew Price, et al. ∙ 3 ∙ share

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To Learn or Not to Learn: Analyzing the Role of Learning for Navigation in Virtual Environments

In this paper we compare learning-based methods and classical methods fo...
07/26/2019 ∙ by Noriyuki Kojima, et al. ∙ 3 ∙ share

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DNNSurv: Deep Neural Networks for Survival Analysis Using Pseudo Values

There has been increasing interest in modelling survival data using deep...
08/06/2019 ∙ by Lili Zhao, et al. ∙ 3 ∙ share

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Learning physics-based reduced-order models for a single-injector combustion process

This paper presents a physics-based data-driven method to learn predicti...
08/09/2019 ∙ by Renee Swischuk, et al. ∙ 3 ∙ share

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Learning Single-Image Depth from Videos using Quality Assessment Networks

Although significant progress has been made in recent years, depth estim...
06/25/2018 ∙ by Weifeng Chen, et al. ∙ 2 ∙ share

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Learning Hierarchical Semantic Image Manipulation through Structured Representations

Understanding, reasoning, and manipulating semantic concepts of images h...
08/22/2018 ∙ by Seunghoon Hong, et al. ∙ 2 ∙ share

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But How Does It Work in Theory? Linear SVM with Random Features

We prove that, under low noise assumptions, the support vector machine w...
09/12/2018 ∙ by Anna Gilbert, et al. ∙ 2 ∙ share

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Speaker Naming in Movies

We propose a new model for speaker naming in movies that leverages visua...
09/24/2018 ∙ by Mahmoud Azab, et al. ∙ 2 ∙ share

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On the Optimality of Perturbations in Stochastic and Adversarial Multi-armed Bandit Problems

We investigate the optimality of perturbation based algorithms in the st...
02/02/2019 ∙ by Baekjin Kim, et al. ∙ 2 ∙ share

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A CNN-based tool for automatic tongue contour tracking in ultrasound images

For speech research, ultrasound tongue imaging provides a non-invasive m...
07/24/2019 ∙ by Jian Zhu, et al. ∙ 2 ∙ share

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Method of Contraction-Expansion (MOCE) for Simultaneous Inference in Linear Models

Simultaneous inference after model selection is of critical importance t...
08/04/2019 ∙ by Fei Wang, et al. ∙ 2 ∙ share

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