ibm

∙ Armonk , United States ∙ 0 followers

International Business Machines Corporation is an American multinational information technology company headquartered in Armonk, New York, with operations in over 170 countries.

Featured Researchers

Wei Liu
243 publications
Wei Zhang
205 publications
Rui Zhang
163 publications
Jun Zhu
131 publications
Li Zhang
126 publications
Bo Zhang
122 publications
Yang Zhang
110 publications
Jie Chen
108 publications
Xiaodan Liang
107 publications
Pin-Yu Chen
99 publications
Yu Cheng
97 publications

When Machine Learning Meets Quantum Computers: A Case Study

Along with the development of AI democratization, the machine learning a...
12/18/2020 ∙ by Weiwen Jiang, et al. ∙ 106 ∙ share

read it
A Possible Reason for why Data-Driven Beats Theory-Driven Computer Vision

Why do some continue to wonder about the success and dominance of deep l...
08/28/2019 ∙ by John K. Tsotsos, et al. ∙ 82 ∙ share

read it
How Data Scientists Work Together With Domain Experts in Scientific Collaborations: To Find The Right Answer Or To Ask The Right Question?

In recent years there has been an increasing trend in which data scienti...
09/08/2019 ∙ by Yaoli Mao, et al. ∙ 72 ∙ share

read it
Unsupervised Temporal Feature Aggregation for Event Detection in Unstructured Sports Videos

Image-based sports analytics enable automatic retrieval of key events in...
02/19/2020 ∙ by Subhajit Chaudhury, et al. ∙ 57 ∙ share

read it
Map Generation from Large Scale Incomplete and Inaccurate Data Labels

Accurately and globally mapping human infrastructure is an important and...
05/20/2020 ∙ by Rui Zhang, et al. ∙ 57 ∙ share

read it
Deep Networks Incorporating Spiking Neural Dynamics

Neural networks have become the key technology of Artificial Intelligenc...
12/17/2018 ∙ by Stanisław Woźniak, et al. ∙ 48 ∙ share

read it
The Emerging Landscape of Explainable AI Planning and Decision Making

In this paper, we provide a comprehensive outline of the different threa...
02/26/2020 ∙ by Tathagata Chakraborti, et al. ∙ 47 ∙ share

read it
Large Graph Convolutional Network Training with GPU-Oriented Data Communication Architecture

Graph Convolutional Networks (GCNs) are increasingly adopted in large-sc...
03/04/2021 ∙ by Seung Won Min, et al. ∙ 45 ∙ share

read it
Embedding Compression with Isotropic Iterative Quantization

Continuous representation of words is a standard component in deep learn...
01/11/2020 ∙ by Siyu Liao, et al. ∙ 36 ∙ share

read it
A Deep Ensemble Multi-Agent Reinforcement Learning Approach for Air Traffic Control

Air traffic control is an example of a highly challenging operational pr...
04/03/2020 ∙ by Supriyo Ghosh, et al. ∙ 32 ∙ share

read it
Chart Auto-Encoders for Manifold Structured Data

Auto-encoding and generative models have made tremendous successes in im...
12/20/2019 ∙ by Stefan Schonsheck, et al. ∙ 31 ∙ share

read it
PAIRS AutoGeo: an Automated Machine Learning Framework for Massive Geospatial Data

An automated machine learning framework for geospatial data named PAIRS ...
12/12/2020 ∙ by Wang Zhou, et al. ∙ 30 ∙ share

read it
Controllability, Multiplexing, and Transfer Learning in Networks using Evolutionary Learning

Networks are fundamental building blocks for representing data, and comp...
11/14/2018 ∙ by Rise Ooi, et al. ∙ 28 ∙ share

read it
Expanding Explainability: Towards Social Transparency in AI systems

As AI-powered systems increasingly mediate consequential decision-making...
01/12/2021 ∙ by Upol Ehsan, et al. ∙ 27 ∙ share

read it
Continual Learning with Self-Organizing Maps

Despite remarkable successes achieved by modern neural networks in a wid...
04/19/2019 ∙ by Pouya Bashivan, et al. ∙ 26 ∙ share

read it
A Dynamical Systems Approach for Convergence of the Bayesian EM Algorithm

Out of the recent advances in systems and control (S&C)-based analysis o...
06/23/2020 ∙ by Orlando Romero, et al. ∙ 26 ∙ share

read it
Temporal Tensor Transformation Network for Multivariate Time Series Prediction

Multivariate time series prediction has applications in a wide variety o...
01/04/2020 ∙ by Yuya Jeremy Ong, et al. ∙ 25 ∙ share

read it
Towards Query-Efficient Black-Box Adversary with Zeroth-Order Natural Gradient Descent

Despite the great achievements of the modern deep neural networks (DNNs)...
02/18/2020 ∙ by Pu Zhao, et al. ∙ 25 ∙ share

read it
How do Data Science Workers Collaborate? Roles, Workflows, and Tools

Today, the prominence of data science within organizations has given ris...
01/18/2020 ∙ by Amy X. Zhang, et al. ∙ 24 ∙ share

read it
A Unified Conversational Assistant Framework for Business Process Automation

Business process automation is a booming multi-billion-dollar industry t...
01/07/2020 ∙ by Yara Rizk, et al. ∙ 23 ∙ share

read it
Visualizing and Understanding Generative Adversarial Networks (Extended Abstract)

Generative Adversarial Networks (GANs) have achieved impressive results ...
01/29/2019 ∙ by David Bau, et al. ∙ 22 ∙ share

read it
Verifiably Safe Exploration for End-to-End Reinforcement Learning

Deploying deep reinforcement learning in safety-critical settings requir...
07/02/2020 ∙ by Nathan Hunt, et al. ∙ 22 ∙ share

read it
Semantic Photo Manipulation with a Generative Image Prior

Despite the recent success of GANs in synthesizing images conditioned on...
05/15/2020 ∙ by David Bau, et al. ∙ 21 ∙ share

read it
Designing Environments Conducive to Interpretable Robot Behavior

Designing robots capable of generating interpretable behavior is a prere...
07/02/2020 ∙ by Anagha Kulkarni, et al. ∙ 21 ∙ share

read it
Chest X-ray Report Generation through Fine-Grained Label Learning

Obtaining automated preliminary read reports for common exams such as ch...
07/27/2020 ∙ by Tanveer Syeda-Mahmood, et al. ∙ 21 ∙ share

read it
Discrete Graph Structure Learning for Forecasting Multiple Time Series

Time series forecasting is an extensively studied subject in statistics,...
01/18/2021 ∙ by Chao Shang, et al. ∙ 21 ∙ share

read it
EvolveGCN: Evolving Graph Convolutional Networks for Dynamic Graphs

Graph representation learning resurges as a trending research subject ow...
02/26/2019 ∙ by Aldo Pareja, et al. ∙ 20 ∙ share

read it
D3BA: A Tool for Optimizing Business Processes Using Non-Deterministic Planning

This paper builds upon recent work in the declarative design of dialogue...
01/08/2020 ∙ by Tathagata Chakraborti, et al. ∙ 20 ∙ share

read it
Automatic Diagnosis of Pulmonary Embolism Using an Attention-guided Framework: A Large-scale Study

Pulmonary Embolism (PE) is a life-threatening disorder associated with h...
05/29/2020 ∙ by Luyao Shi, et al. ∙ 20 ∙ share

read it
Drill-down: Interactive Retrieval of Complex Scenes using Natural Language Queries

This paper explores the task of interactive image retrieval using natura...
11/10/2019 ∙ by Fuwen Tan, et al. ∙ 19 ∙ share

read it
Interpretable Deep Graph Generation with Node-Edge Co-Disentanglement

Disentangled representation learning has recently attracted a significan...
06/09/2020 ∙ by Xiaojie Guo, et al. ∙ 19 ∙ share

read it
Dynamic Knowledge Distillation for Black-box Hypothesis Transfer Learning

In real world applications like healthcare, it is usually difficult to b...
07/24/2020 ∙ by Yiqin Yu, et al. ∙ 19 ∙ share

read it
Planning with Explanatory Actions: A Joint Approach to Plan Explicability and Explanations in Human-Aware Planning

In this work, we formulate the process of generating explanations as mod...
03/18/2019 ∙ by Sarath Sreedharan, et al. ∙ 18 ∙ share

read it
A Study of Compositional Generalization in Neural Models

Compositional and relational learning is a hallmark of human intelligenc...
06/16/2020 ∙ by Tim Klinger, et al. ∙ 18 ∙ share

read it
Building medical image classifiers with very limited data using segmentation networks

Deep learning has shown promising results in medical image analysis, how...
08/15/2018 ∙ by Ken C. L. Wong, et al. ∙ 16 ∙ share

read it
Interpretable Multi-Objective Reinforcement Learning through Policy Orchestration

Autonomous cyber-physical agents and systems play an increasingly large ...
09/21/2018 ∙ by Ritesh Noothigattu, et al. ∙ 16 ∙ share

read it
Recognizing Disguised Faces in the Wild

Research in face recognition has seen tremendous growth over the past co...
11/21/2018 ∙ by Maneet Singh, et al. ∙ 16 ∙ share

read it
Toward A Neuro-inspired Creative Decoder

Creativity, a process that generates novel and valuable ideas, involves ...
02/06/2019 ∙ by Payel Das, et al. ∙ 16 ∙ share

read it
Improving Efficiency in Large-Scale Decentralized Distributed Training

Decentralized Parallel SGD (D-PSGD) and its asynchronous variant Asynchr...
02/04/2020 ∙ by Wei Zhang, et al. ∙ 16 ∙ share

read it
Link Prediction using Graph Neural Networks for Master Data Management

Learning graph representations of n-ary relational data has a number of ...
03/07/2020 ∙ by Balaji Ganesan, et al. ∙ 16 ∙ share

read it
Testing Framework for Black-box AI Models

With widespread adoption of AI models for important decision making, ens...
02/11/2021 ∙ by Aniya Aggarwal, et al. ∙ 16 ∙ share

read it
A Novel Methodology For Crowdsourcing AI Models in an Enterprise

The evolution of AI is advancing rapidly, creating both challenges and o...
03/22/2021 ∙ by Parthasarathy Suryanarayanan, et al. ∙ 16 ∙ share

read it
CPDist: Deep Siamese Networks for Learning Distances Between Structured Preferences

Preference are central to decision making by both machines and humans. R...
09/21/2018 ∙ by Andrea Loreggia, et al. ∙ 14 ∙ share

read it
Learning to Remember, Forget and Ignore using Attention Control in Memory

Typical neural networks with external memory do not effectively separate...
09/28/2018 ∙ by T. S. Jayram, et al. ∙ 14 ∙ share

read it
Neural network gradient-based learning of black-box function interfaces

Deep neural networks work well at approximating complicated functions wh...
01/13/2019 ∙ by Alon Jacovi, et al. ∙ 14 ∙ share

read it
AVLnet: Learning Audio-Visual Language Representations from Instructional Videos

Current methods for learning visually grounded language from videos ofte...
06/16/2020 ∙ by Andrew Rouditchenko, et al. ∙ 14 ∙ share

read it
Gi and Pal Scores: Deep Neural Network Generalization Statistics

The field of Deep Learning is rich with empirical evidence of human-like...
04/08/2021 ∙ by Yair Schiff, et al. ∙ 14 ∙ share

read it
Is Robustness the Cost of Accuracy? -- A Comprehensive Study on the Robustness of 18 Deep Image Classification Models

The prediction accuracy has been the long-lasting and sole standard for ...
08/05/2018 ∙ by Dong Su, et al. ∙ 12 ∙ share

read it
Using Multi-task and Transfer Learning to Solve Working Memory Tasks

We propose a new architecture called Memory-Augmented Encoder-Solver (MA...
09/28/2018 ∙ by T. S. Jayram, et al. ∙ 12 ∙ share

read it
sZoom: A Framework for Automatic Zoom into High Resolution Surveillance Videos

Current cameras are capable of recording high resolution video. While vi...
09/23/2019 ∙ by Mukesh Saini, et al. ∙ 12 ∙ share

read it