Microsoft

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Microsoft Corporation is a technology company. The Company develops, licenses, and supports a range of software products, services and devices. The Company's segments include Productivity and Business Processes, Intelligent Cloud and More Personal Computing. The Company's products include operating systems; cross-device productivity applications; server applications; business solution applications; desktop and server management tools; software development tools; video games, and training and certification of computer system integrators and developers. It also designs, manufactures, and sells devices, including personal computers (PCs), tablets, gaming and entertainment consoles, phones, other intelligent devices, and related accessories, that integrate with its cloud-based offerings. It offers an array of services, including cloud-based solutions that provide customers with software, services, platforms, and content, and it provides solution support and consulting services.

Featured Researchers

Yang Liu
231 publications
Wei Liu
181 publications
Wei Wang
167 publications
Lei Zhang
141 publications
Wei Zhang
133 publications
Jun Wang
129 publications
Jianfeng Gao
105 publications
Wei Li
104 publications
Rui Wang
96 publications
Wei Chen
89 publications
Yi Zhang
87 publications

FLO: Fast and Lightweight Hyperparameter Optimization for AutoML

Integrating ML models in software is of growing interest. Building accur...
11/12/2019 ∙ by Chi Wang, et al. ∙ 58 ∙ share

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Unsupervised Domain Adaptation for Object Detection via Cross-Domain Semi-Supervised Learning

Current state-of-the-art object detectors can have significant performan...
11/17/2019 ∙ by Fuxun Yu, et al. ∙ 47 ∙ share

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On the Anomalous Generalization of GANs

Generative models, especially Generative Adversarial Networks (GANs), ha...
09/27/2019 ∙ by Jinchen Xuan, et al. ∙ 46 ∙ share

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360-Indoor: Towards Learning Real-World Objects in 360° Indoor Equirectangular Images

While there are several widely used object detection datasets, current c...
10/03/2019 ∙ by Shih-Han Chou, et al. ∙ 46 ∙ share

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Relationship-Aware Spatial Perception Fusion for Realistic Scene Layout Generation

The significant progress on Generative Adversarial Networks (GANs) have ...
09/02/2019 ∙ by Hongdong Zheng, et al. ∙ 44 ∙ share

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SQuINTing at VQA Models: Interrogating VQA Models with Sub-Questions

Existing VQA datasets contain questions with varying levels of complexit...
01/20/2020 ∙ by Ramprasaath R. Selvaraju, et al. ∙ 44 ∙ share

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D2D-Enabled Data Sharing for Distributed Machine Learning at Wireless Network Edge

Mobile edge learning is an emerging technique that enables distributed e...
01/28/2020 ∙ by Xiaoran Cai, et al. ∙ 42 ∙ share

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MixPath: A Unified Approach for One-shot Neural Architecture Search

The expressiveness of search space is a key concern in neural architectu...
01/16/2020 ∙ by Xiangxiang Chu, et al. ∙ 39 ∙ share

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Minmax Optimization: Stable Limit Points of Gradient Descent Ascent are Locally Optimal

Minmax optimization, especially in its general nonconvex-nonconcave form...
02/02/2019 ∙ by Chi Jin, et al. ∙ 34 ∙ share

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Appending Adversarial Frames for Universal Video Attack

There have been many efforts in attacking image classification models wi...
12/10/2019 ∙ by Zhikai Chen, et al. ∙ 34 ∙ share

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DSRGAN: Explicitly Learning Disentangled Representation of Underlying Structure and Rendering for Image Generation without Tuple Supervision

We focus on explicitly learning disentangled representation for natural ...
09/30/2019 ∙ by Guang-Yuan Hao, et al. ∙ 33 ∙ share

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Learning Pyramid-Context Encoder Network for High-Quality Image Inpainting

High-quality image inpainting requires filling missing regions in a dama...
04/16/2019 ∙ by Yanhong Zeng, et al. ∙ 32 ∙ share

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Learning Spatial Awareness to Improve Crowd Counting

The aim of crowd counting is to estimate the number of people in images ...
09/16/2019 ∙ by Zhi-Qi Cheng, et al. ∙ 32 ∙ share

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Instance-wise Depth and Motion Learning from Monocular Videos

We present an end-to-end joint training framework that explicitly models...
12/19/2019 ∙ by Seokju Lee, et al. ∙ 30 ∙ share

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Non-local Recurrent Neural Memory for Supervised Sequence Modeling

Typical methods for supervised sequence modeling are built upon the recu...
08/26/2019 ∙ by Canmiao Fu, et al. ∙ 29 ∙ share

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An Anatomy of Graph Neural Networks Going Deep via the Lens of Mutual Information: Exponential Decay vs. Full Preservation

Graph Convolutional Network (GCN) has attracted intensive interests rece...
10/10/2019 ∙ by Nezihe Merve Gürel, et al. ∙ 28 ∙ share

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Learn to Expect the Unexpected: Probably Approximately Correct Domain Generalization

Domain generalization is the problem of machine learning when the traini...
02/13/2020 ∙ by Vikas K. Garg, et al. ∙ 26 ∙ share

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The Non-IID Data Quagmire of Decentralized Machine Learning

Many large-scale machine learning (ML) applications need to train ML mod...
10/01/2019 ∙ by Kevin Hsieh, et al. ∙ 25 ∙ share

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Densely Semantically Aligned Person Re-Identification

We propose a densely semantically aligned person re-identification (re-I...
12/21/2018 ∙ by Zhizheng Zhang, et al. ∙ 24 ∙ share

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Logic Rules Powered Knowledge Graph Embedding

Large scale knowledge graph embedding has attracted much attention from ...
03/09/2019 ∙ by Pengwei Wang, et al. ∙ 24 ∙ share

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Learning Residual Flow as Dynamic Motion from Stereo Videos

We present a method for decomposing the 3D scene flow observed from a mo...
09/16/2019 ∙ by Seokju Lee, et al. ∙ 24 ∙ share

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Affect-based Intrinsic Rewards for Learning General Representations

Positive affect has been linked to increased interest, curiosity and sat...
12/01/2019 ∙ by Dean Zadok, et al. ∙ 24 ∙ share

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Towards Omni-Supervised Face Alignment for Large Scale Unlabeled Videos

In this paper, we propose a spatial-temporal relational reasoning networ...
12/16/2019 ∙ by Congcong Zhu, et al. ∙ 24 ∙ share

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Animating Face using Disentangled Audio Representations

All previous methods for audio-driven talking head generation assume the...
10/02/2019 ∙ by Gaurav Mittal, et al. ∙ 23 ∙ share

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RNNbow: Visualizing Learning via Backpropagation Gradients in Recurrent Neural Networks

We present RNNbow, an interactive tool for visualizing the gradient flow...
07/29/2019 ∙ by Dylan Cashman, et al. ∙ 22 ∙ share

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Disentangling Interpretable Generative Parameters of Random and Real-World Graphs

While a wide range of interpretable generative procedures for graphs exi...
10/12/2019 ∙ by Niklas Stoehr, et al. ∙ 22 ∙ share

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Learning Calibratable Policies using Programmatic Style-Consistency

We study the important and challenging problem of controllable generatio...
10/02/2019 ∙ by Eric Zhan, et al. ∙ 21 ∙ share

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Deformable Kernels: Adapting Effective Receptive Fields for Object Deformation

Convolutional networks are not aware of an object's geometric variations...
10/07/2019 ∙ by Hang Gao, et al. ∙ 21 ∙ share

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STANCY: Stance Classification Based on Consistency Cues

Controversial claims are abundant in online media and discussion forums....
10/14/2019 ∙ by Kashyap Popat, et al. ∙ 21 ∙ share

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Resource-Efficient Neural Networks for Embedded Systems

While machine learning is traditionally a resource intensive task, embed...
01/07/2020 ∙ by Wolfgang Roth, et al. ∙ 21 ∙ share

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Stochastic Gradient Descent Escapes Saddle Points Efficiently

This paper considers the perturbed stochastic gradient descent algorithm...
02/13/2019 ∙ by Chi Jin, et al. ∙ 20 ∙ share

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Stochastic Online Learning with Probabilistic Graph Feedback

We consider a problem of stochastic online learning with general probabi...
03/04/2019 ∙ by Shuai Li, et al. ∙ 20 ∙ share

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Accurate 3D Face Reconstruction with Weakly-Supervised Learning: From Single Image to Image Set

Recently, deep learning based 3D face reconstruction methods have shown ...
03/20/2019 ∙ by Yu Deng, et al. ∙ 20 ∙ share

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DBRec: Dual-Bridging Recommendation via Discovering Latent Groups

In recommender systems, the user-item interaction data is usually sparse...
09/27/2019 ∙ by Jingwei Ma, et al. ∙ 20 ∙ share

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Conditional Self-Attention for Query-based Summarization

Self-attention mechanisms have achieved great success on a variety of NL...
02/18/2020 ∙ by Yujia Xie, et al. ∙ 20 ∙ share

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Tightening Bounds for Variational Inference by Revisiting Perturbation Theory

Variational inference has become one of the most widely used methods in ...
09/30/2019 ∙ by Robert Bamler, et al. ∙ 19 ∙ share

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Deeper Insights into Weight Sharing in Neural Architecture Search

With the success of deep neural networks, Neural Architecture Search (NA...
01/06/2020 ∙ by Yuge Zhang, et al. ∙ 19 ∙ share

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Image Smoothing via Unsupervised Learning

Image smoothing represents a fundamental component of many disparate com...
11/07/2018 ∙ by Qingnan Fan, et al. ∙ 18 ∙ share

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Learning Visual Relation Priors for Image-Text Matching and Image Captioning with Neural Scene Graph Generators

Grounding language to visual relations is critical to various language-a...
09/22/2019 ∙ by Kuang-Huei Lee, et al. ∙ 18 ∙ share

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Reasoning Over Semantic-Level Graph for Fact Checking

We study fact-checking in this paper, which aims to verify a textual cla...
09/09/2019 ∙ by Wanjun Zhong, et al. ∙ 17 ∙ 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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Gated Context Aggregation Network for Image Dehazing and Deraining

Image dehazing aims to recover the uncorrupted content from a hazy image...
11/21/2018 ∙ by Dongdong Chen, et al. ∙ 16 ∙ share

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Exploring Hypergraph Representation on Face Anti-spoofing Beyond 2D Attacks

Face anti-spoofing plays a crucial role in protecting face recognition s...
11/28/2018 ∙ by Wei Hu, et al. ∙ 16 ∙ share

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A Short Note on Concentration Inequalities for Random Vectors with SubGaussian Norm

In this note, we derive concentration inequalities for random vectors wi...
02/11/2019 ∙ by Chi Jin, et al. ∙ 16 ∙ share

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Unpaired Image-to-Image Translation with Domain Supervision

Image-to-image translation has been widely investigated in recent years....
02/11/2019 ∙ by Jianxin Lin, et al. ∙ 16 ∙ share

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MT-BioNER: Multi-task Learning for Biomedical Named Entity Recognition using Deep Bidirectional Transformers

Conversational agents such as Cortana, Alexa and Siri are continuously w...
01/24/2020 ∙ by Muhammad Raza Khan, et al. ∙ 15 ∙ share

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Adding Attentiveness to the Neurons in Recurrent Neural Networks

Recurrent neural networks (RNNs) are capable of modeling the temporal dy...
07/12/2018 ∙ by Pengfei Zhang, et al. ∙ 14 ∙ share

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Contextual Face Recognition with a Nested-Hierarchical Nonparametric Identity Model

Current face recognition systems typically operate via classification in...
11/19/2018 ∙ by Daniel C. Castro, et al. ∙ 14 ∙ share

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An Empirical Study of Example Forgetting during Deep Neural Network Learning

Inspired by the phenomenon of catastrophic forgetting, we investigate th...
12/12/2018 ∙ by Mariya Toneva, et al. ∙ 14 ∙ share

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Learning to Prescribe Interventions for Tuberculosis Patients using Digital Adherence Data

Digital Adherence Technologies (DATs) are an increasingly popular method...
02/05/2019 ∙ by Jackson A. Killian, et al. ∙ 14 ∙ share

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