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Spurious Local Minima Are Common for Deep Neural Networks with Piecewise Linear Activations
In this paper, it is shown theoretically that spurious local minima are ...
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SLAKE: A Semantically-Labeled Knowledge-Enhanced Dataset for Medical Visual Question Answering
Medical visual question answering (Med-VQA) has tremendous potential in ...
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Firefly Neural Architecture Descent: a General Approach for Growing Neural Networks
We propose firefly neural architecture descent, a general framework for ...
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Motion Control for Mobile Robot Navigation Using Machine Learning: a Survey
Moving in complex environments is an essential capability of intelligent...
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Towards Playing Full MOBA Games with Deep Reinforcement Learning
MOBA games, e.g., Honor of Kings, League of Legends, and Dota 2, pose gr...
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When Machine Learning Meets Privacy: A Survey and Outlook
The newly emerged machine learning (e.g. deep learning) methods have bec...
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Experimental implementation of secure anonymous protocols on an eight-user quantum network
Anonymity in networked communication is vital for many privacy-preservin...
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The SLT 2021 children speech recognition challenge: Open datasets, rules and baselines
Automatic speech recognition (ASR) has been significantly advanced with ...
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APPLI: Adaptive Planner Parameter Learning From Interventions
While classical autonomous navigation systems can typically move robots ...
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APPLR: Adaptive Planner Parameter Learning from Reinforcement
Classical navigation systems typically operate using a fixed set of hand...
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Human versus Machine Attention in Deep Reinforcement Learning Tasks
Deep reinforcement learning (RL) algorithms are powerful tools for solvi...
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Continuous-time Gaussian Process Trajectory Generation for Multi-robot Formation via Probabilistic Inference
In this paper, we extend a famous motion planning approach GPMP2 to mult...
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An Industry Evaluation of Embedding-based Entity Alignment
Embedding-based entity alignment has been widely investigated in recent ...
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Extended Abstract: Motion Planners Learned from Geometric Hallucination
Learning motion planners to move robot from one point to another within ...
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The NVIDIA PilotNet Experiments
Four years ago, an experimental system known as PilotNet became the firs...
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Agile Robot Navigation through Hallucinated Learning and Sober Deployment
Learning from Hallucination (LfH) is a recent machine learning paradigm ...
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Identifying Melanoma Images using EfficientNet Ensemble: Winning Solution to the SIIM-ISIC Melanoma Classification Challenge
We present our winning solution to the SIIM-ISIC Melanoma Classification...
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Google Landmark Recognition 2020 Competition Third Place Solution
We present our third place solution to the Google Landmark Recognition 2...
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Discriminative Segmentation Tracking Using Dual Memory Banks
Existing template-based trackers usually localize the target in each fra...
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Variance-Reduced Off-Policy Memory-Efficient Policy Search
Off-policy policy optimization is a challenging problem in reinforcement...
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Zero-Shot Learning from Adversarial Feature Residual to Compact Visual Feature
Recently, many zero-shot learning (ZSL) methods focused on learning disc...
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Oriented Object Detection in Aerial Images with Box Boundary-Aware Vectors
Oriented object detection in aerial images is a challenging task as the ...
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Lifelong Navigation
This paper presents a continually self-improving lifelong learning frame...
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Toward Agile Maneuvers in Highly Constrained Spaces: Learning from Hallucination
While classical approaches to autonomous robot navigation currently enab...
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Meta-Learning with Network Pruning
Meta-learning is a powerful paradigm for few-shot learning. Although wit...
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RDP-GAN: A Rényi-Differential Privacy based Generative Adversarial Network
Generative adversarial network (GAN) has attracted increasing attention ...
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Understanding Global Loss Landscape of One-hidden-layer ReLU Networks, Part 2: Experiments and Analysis
The existence of local minima for one-hidden-layer ReLU networks has bee...
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Stable and Efficient Policy Evaluation
Policy evaluation algorithms are essential to reinforcement learning due...
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Proximal Gradient Temporal Difference Learning: Stable Reinforcement Learning with Polynomial Sample Complexity
In this paper, we introduce proximal gradient temporal difference learni...
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Regularized Off-Policy TD-Learning
We present a novel l_1 regularized off-policy convergent TD-learning met...
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Fast Enhancement for Non-Uniform Illumination Images using Light-weight CNNs
This paper proposes a new light-weight convolutional neural network (5k ...
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A Light-Weighted Convolutional Neural Network for Bitemporal SAR Image Change Detection
Recently, many Convolution Neural Networks (CNN) have been successfully ...
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Few-Shot Open-Set Recognition using Meta-Learning
The problem of open-set recognition is considered. While previous approa...
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A Convolutional Neural Network with Parallel Multi-Scale Spatial Pooling to Detect Temporal Changes in SAR Images
In synthetic aperture radar (SAR) image change detection, it is quite ch...
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Per-Step Reward: A New Perspective for Risk-Averse Reinforcement Learning
We present a new per-step reward perspective for risk-averse control in ...
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APPLD: Adaptive Planner Parameter Learning from Demonstration
Existing autonomous robot navigation systems allow robots to move from o...
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Exploit Clues from Views: Self-Supervised and Regularized Learning for Multiview Object Recognition
Multiview recognition has been well studied in the literature and achiev...
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Adaptive Graph Convolutional Network with Attention Graph Clustering for Co-saliency Detection
Co-saliency detection aims to discover the common and salient foreground...
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Dual Temporal Memory Network for Efficient Video Object Segmentation
Video Object Segmentation (VOS) is typically formulated in a semi-superv...
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Shannon-Limit Approached Information Reconciliation for Quantum Key Distribution
Information reconciliation (IR) corrects the errors in sifted keys and e...
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Geometry and Topology of Deep Neural Networks' Decision Boundaries
Geometry and topology of decision regions are closely related with class...
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Understanding Global Loss Landscape of One-hidden-layer ReLU Neural Networks
For one-hidden-layer ReLU networks, we show that all local minima are gl...
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GradientDICE: Rethinking Generalized Offline Estimation of Stationary Values
We present GradientDICE for estimating the density ratio between the sta...
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Video Saliency Prediction Using Enhanced Spatiotemporal Alignment Network
Due to a variety of motions across different frames, it is highly challe...
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Deep Object Co-segmentation via Spatial-Semantic Network Modulation
Object co-segmentation is to segment the shared objects in multiple rele...
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Robust Conditional GAN from Uncertainty-Aware Pairwise Comparisons
Conditional generative adversarial networks have shown exceptional gener...
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Object-Guided Instance Segmentation for Biological Images
Instance segmentation of biological images is essential for studying obj...
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Heterogeneous Deep Graph Infomax
Graph representation learning is to learn universal node representations...
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FeCaffe: FPGA-enabled Caffe with OpenCL for Deep Learning Training and Inference on Intel Stratix 10
Deep learning and Convolutional Neural Network (CNN) have becoming incre...
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Provably Convergent Off-Policy Actor-Critic with Function Approximation
We present the first provably convergent off-policy actor-critic algorit...
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