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When Machine Learning Meets Quantum Computers: A Case Study
Along with the development of AI democratization, the machine learning a...
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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...
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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...
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Unsupervised Temporal Feature Aggregation for Event Detection in Unstructured Sports Videos
Image-based sports analytics enable automatic retrieval of key events in...
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Map Generation from Large Scale Incomplete and Inaccurate Data Labels
Accurately and globally mapping human infrastructure is an important and...
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Deep Networks Incorporating Spiking Neural Dynamics
Neural networks have become the key technology of Artificial Intelligenc...
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The Emerging Landscape of Explainable AI Planning and Decision Making
In this paper, we provide a comprehensive outline of the different threa...
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Embedding Compression with Isotropic Iterative Quantization
Continuous representation of words is a standard component in deep learn...
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A Deep Ensemble Multi-Agent Reinforcement Learning Approach for Air Traffic Control
Air traffic control is an example of a highly challenging operational pr...
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Chart Auto-Encoders for Manifold Structured Data
Auto-encoding and generative models have made tremendous successes in im...
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PAIRS AutoGeo: an Automated Machine Learning Framework for Massive Geospatial Data
An automated machine learning framework for geospatial data named PAIRS ...
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Controllability, Multiplexing, and Transfer Learning in Networks using Evolutionary Learning
Networks are fundamental building blocks for representing data, and comp...
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Expanding Explainability: Towards Social Transparency in AI systems
As AI-powered systems increasingly mediate consequential decision-making...
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Continual Learning with Self-Organizing Maps
Despite remarkable successes achieved by modern neural networks in a wid...
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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...
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Temporal Tensor Transformation Network for Multivariate Time Series Prediction
Multivariate time series prediction has applications in a wide variety o...
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Towards Query-Efficient Black-Box Adversary with Zeroth-Order Natural Gradient Descent
Despite the great achievements of the modern deep neural networks (DNNs)...
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How do Data Science Workers Collaborate? Roles, Workflows, and Tools
Today, the prominence of data science within organizations has given ris...
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A Unified Conversational Assistant Framework for Business Process Automation
Business process automation is a booming multi-billion-dollar industry t...
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Visualizing and Understanding Generative Adversarial Networks (Extended Abstract)
Generative Adversarial Networks (GANs) have achieved impressive results ...
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Verifiably Safe Exploration for End-to-End Reinforcement Learning
Deploying deep reinforcement learning in safety-critical settings requir...
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Semantic Photo Manipulation with a Generative Image Prior
Despite the recent success of GANs in synthesizing images conditioned on...
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Designing Environments Conducive to Interpretable Robot Behavior
Designing robots capable of generating interpretable behavior is a prere...
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Chest X-ray Report Generation through Fine-Grained Label Learning
Obtaining automated preliminary read reports for common exams such as ch...
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EvolveGCN: Evolving Graph Convolutional Networks for Dynamic Graphs
Graph representation learning resurges as a trending research subject ow...
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D3BA: A Tool for Optimizing Business Processes Using Non-Deterministic Planning
This paper builds upon recent work in the declarative design of dialogue...
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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...
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Drill-down: Interactive Retrieval of Complex Scenes using Natural Language Queries
This paper explores the task of interactive image retrieval using natura...
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Interpretable Deep Graph Generation with Node-Edge Co-Disentanglement
Disentangled representation learning has recently attracted a significan...
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Dynamic Knowledge Distillation for Black-box Hypothesis Transfer Learning
In real world applications like healthcare, it is usually difficult to b...
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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...
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A Study of Compositional Generalization in Neural Models
Compositional and relational learning is a hallmark of human intelligenc...
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Building medical image classifiers with very limited data using segmentation networks
Deep learning has shown promising results in medical image analysis, how...
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Interpretable Multi-Objective Reinforcement Learning through Policy Orchestration
Autonomous cyber-physical agents and systems play an increasingly large ...
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Recognizing Disguised Faces in the Wild
Research in face recognition has seen tremendous growth over the past co...
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Toward A Neuro-inspired Creative Decoder
Creativity, a process that generates novel and valuable ideas, involves ...
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Improving Efficiency in Large-Scale Decentralized Distributed Training
Decentralized Parallel SGD (D-PSGD) and its asynchronous variant Asynchr...
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Link Prediction using Graph Neural Networks for Master Data Management
Learning graph representations of n-ary relational data has a number of ...
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CPDist: Deep Siamese Networks for Learning Distances Between Structured Preferences
Preference are central to decision making by both machines and humans. R...
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Learning to Remember, Forget and Ignore using Attention Control in Memory
Typical neural networks with external memory do not effectively separate...
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Neural network gradient-based learning of black-box function interfaces
Deep neural networks work well at approximating complicated functions wh...
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AVLnet: Learning Audio-Visual Language Representations from Instructional Videos
Current methods for learning visually grounded language from videos ofte...
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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 ...
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Using Multi-task and Transfer Learning to Solve Working Memory Tasks
We propose a new architecture called Memory-Augmented Encoder-Solver (MA...
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sZoom: A Framework for Automatic Zoom into High Resolution Surveillance Videos
Current cameras are capable of recording high resolution video. While vi...
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Model Agnostic Contrastive Explanations for Structured Data
Recently, a method [7] was proposed to generate contrastive explanations...
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SimVAE: Simulator-Assisted Training forInterpretable Generative Models
This paper presents a simulator-assisted training method (SimVAE) for va...
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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...
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Kernel Stein Generative Modeling
We are interested in gradient-based Explicit Generative Modeling where s...
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Practical Detection of Trojan Neural Networks: Data-Limited and Data-Free Cases
When the training data are maliciously tampered, the predictions of the ...
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