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.

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. ∙ 71 ∙ 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
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
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
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
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
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
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
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
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. ∙ 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
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
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
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
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
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
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
Model Agnostic Contrastive Explanations for Structured Data

Recently, a method [7] was proposed to generate contrastive explanations...
05/31/2019 ∙ by Amit Dhurandhar, et al. ∙ 11 ∙ share

read it
SimVAE: Simulator-Assisted Training forInterpretable Generative Models

This paper presents a simulator-assisted training method (SimVAE) for va...
11/19/2019 ∙ by Akash Srivastava, et al. ∙ 11 ∙ share

read it
TS2C: Tight Box Mining with Surrounding Segmentation Context for Weakly Supervised Object Detection

This work provides a simple approach to discover tight object bounding b...
07/13/2018 ∙ by Yunchao Wei, et al. ∙ 10 ∙ share

read it
Safe Exploration in Markov Decision Processes with Time-Variant Safety using Spatio-Temporal Gaussian Process

In many real-world applications (e.g., planetary exploration, robot navi...
09/12/2018 ∙ by Akifumi Wachi, et al. ∙ 10 ∙ share

read it
Image-Level Attentional Context Modeling Using Nested-Graph Neural Networks

We introduce a new scene graph generation method called image-level atte...
11/09/2018 ∙ by Guillaume Jaume, et al. ∙ 10 ∙ share

read it
A deep learning approach to solar-irradiance forecasting in sky-videos

Ahead-of-time forecasting of incident solar-irradiance on a panel is ind...
01/15/2019 ∙ by Talha A. Siddiqui, et al. ∙ 10 ∙ share

read it
Learning Embeddings into Entropic Wasserstein Spaces

Euclidean embeddings of data are fundamentally limited in their ability ...
05/08/2019 ∙ by Charlie Frogner, et al. ∙ 10 ∙ share

read it
AutoGAN: Neural Architecture Search for Generative Adversarial Networks

Neural architecture search (NAS) has witnessed prevailing success in ima...
08/11/2019 ∙ by Xinyu Gong, et al. ∙ 10 ∙ share

read it
CAG: A Real-time Low-cost Enhanced-robustness High-transferability Content-aware Adversarial Attack Generator

Deep neural networks (DNNs) are vulnerable to adversarial attack despite...
12/16/2019 ∙ by Huy Phan, et al. ∙ 10 ∙ share

read it
Bio-Inspired Hashing for Unsupervised Similarity Search

The fruit fly Drosophila's olfactory circuit has inspired a new locality...
01/14/2020 ∙ by Chaitanya K. Ryali, et al. ∙ 10 ∙ share

read it
PoWER-BERT: Accelerating BERT inference for Classification Tasks

BERT has emerged as a popular model for natural language understanding. ...
01/24/2020 ∙ by Saurabh Goyal, et al. ∙ 10 ∙ share

read it
Joint Optimization of AI Fairness and Utility: A Human-Centered Approach

Today, AI is increasingly being used in many high-stakes decision-making...
02/05/2020 ∙ by Yunfeng Zhang, et al. ∙ 10 ∙ share

read it
Query-Efficient Hard-label Black-box Attack:An Optimization-based Approach

We study the problem of attacking a machine learning model in the hard-l...
07/12/2018 ∙ by Minhao Cheng, et al. ∙ 8 ∙ share

read it
Improving Transferability of Deep Neural Networks

Learning from small amounts of labeled data is a challenge in the area o...
07/30/2018 ∙ by Parijat Dube, et al. ∙ 8 ∙ share

read it
Improving Natural Language Inference Using External Knowledge in the Science Questions Domain

Natural Language Inference (NLI) is fundamental to many Natural Language...
09/15/2018 ∙ by Xiaoyan Wang, et al. ∙ 8 ∙ share

read it
Efficient Neural Network Robustness Certification with General Activation Functions

Finding minimum distortion of adversarial examples and thus certifying r...
11/02/2018 ∙ by Huan Zhang, et al. ∙ 8 ∙ share

read it
Building Ethically Bounded AI

The more AI agents are deployed in scenarios with possibly unexpected si...
12/10/2018 ∙ by Francesca Rossi, et al. ∙ 8 ∙ share

read it
Few-shot Learning with Meta Metric Learners

Few-shot Learning aims to learn classifiers for new classes with only a ...
01/26/2019 ∙ by Yu Cheng, et al. ∙ 8 ∙ share

read it
Hybrid Reinforcement Learning with Expert State Sequences

Existing imitation learning approaches often require that the complete d...
03/11/2019 ∙ by Xiaoxiao Guo, et al. ∙ 8 ∙ share

read it
A Highly Efficient Distributed Deep Learning System For Automatic Speech Recognition

Modern Automatic Speech Recognition (ASR) systems rely on distributed de...
07/10/2019 ∙ by Wei Zhang, et al. ∙ 8 ∙ share

read it
Ensemble Knowledge Distillation for Learning Improved and Efficient Networks

Ensemble models comprising of deep Convolutional Neural Networks (CNN) h...
09/17/2019 ∙ by Umar Asif, et al. ∙ 8 ∙ share

read it
Expecting the Unexpected: Developing Autonomous-System Design Principles for Reacting to Unpredicted Events and Conditions

When developing autonomous systems, engineers and other stakeholders mak...
01/16/2020 ∙ by Assaf Marron, et al. ∙ 8 ∙ share

read it

ibm

Featured Researchers