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Incremental Learning via Rate Reduction
Current deep learning architectures suffer from catastrophic forgetting,...
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Deep Networks from the Principle of Rate Reduction
This work attempts to interpret modern deep (convolutional) networks fro...
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HoliCity: A City-Scale Data Platform for Learning Holistic 3D Structures
We present HoliCity, a city-scale 3D dataset with rich structural inform...
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Learning Long-term Visual Dynamics with Region Proposal Interaction Networks
Learning long-term dynamics models is the key to understanding physical ...
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Learning to Parse Wireframes in Images of Man-Made Environments
In this paper, we propose a learning-based approach to the task of autom...
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Deep Isometric Learning for Visual Recognition
Initialization, normalization, and skip connections are believed to be t...
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Dynamic Knapsack Optimization Towards Efficient Multi-Channel Sequential Advertising
In E-commerce, advertising is essential for merchants to reach their tar...
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Stochastic Variance Reduction via Accelerated Dual Averaging for Finite-Sum Optimization
In this paper, we introduce a simplified and unified method for finite-s...
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Learning to Detect 3D Reflection Symmetry for Single-View Reconstruction
3D reconstruction from a single RGB image is a challenging problem in co...
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Robust Recovery via Implicit Bias of Discrepant Learning Rates for Double Over-parameterization
Recent advances have shown that implicit bias of gradient descent on ove...
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Learning Diverse and Discriminative Representations via the Principle of Maximal Coding Rate Reduction
To learn intrinsic low-dimensional structures from high-dimensional data...
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Learning to Accelerate Heuristic Searching for Large-Scale Maximum Weighted b-Matching Problems in Online Advertising
Bipartite b-matching is fundamental in algorithm design, and has been wi...
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On Deep Learning Solutions for Joint Transmitter and Noncoherent Receiver Design in MU-MIMO Systems
This paper aims to handle the joint transmitter and noncoherent receiver...
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A Modular Neural Network Based Deep Learning Approach for MIMO Signal Detection
In this paper, we reveal that artificial neural network (ANN) assisted m...
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Rethinking Bias-Variance Trade-off for Generalization of Neural Networks
The classical bias-variance trade-off predicts that bias decreases and v...
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KoGuN: Accelerating Deep Reinforcement Learning via Integrating Human Suboptimal Knowledge
Reinforcement learning agents usually learn from scratch, which requires...
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An Actor-Critic-Based UAV-BSs Deployment Method for Dynamic Environments
In this paper, the real-time deployment of unmanned aerial vehicles (UAV...
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NeurVPS: Neural Vanishing Point Scanning via Conic Convolution
We present a simple yet effective end-to-end trainable deep network with...
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Spectral-based Graph Convolutional Network for Directed Graphs
Graph convolutional networks(GCNs) have become the most popular approach...
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Complete Dictionary Learning via ℓ^4-Norm Maximization over the Orthogonal Group
This paper considers the fundamental problem of learning a complete (ort...
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Towards Unified Acceleration of High-Order Algorithms under Hölder Continuity and Uniform Convexity
In this paper, through a very intuitive vanilla proximal method perspec...
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Learning to Reconstruct 3D Manhattan Wireframes from a Single Image
In this paper, we propose a method to obtain a compact and accurate 3D w...
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End-to-End Wireframe Parsing
We present a conceptually simple yet effective algorithm to detect wiref...
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Fine-grained Video Categorization with Redundancy Reduction Attention
For fine-grained categorization tasks, videos could serve as a better so...
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TARM: A Turbo-type Algorithm for Affine Rank Minimization
The affine rank minimization (ARM) problem arises in many real-world app...
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Symbol-Level Selective Full-Duplex Relaying with Power and Location Optimization
In this paper, a symbol-level selective transmission for full-duplex (FD...
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Structured Attentions for Visual Question Answering
Visual attention, which assigns weights to image regions according to th...
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Graph Construction with Label Information for Semi-Supervised Learning
In the literature, most existing graph-based semi-supervised learning (S...
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Automatic Layer Separation using Light Field Imaging
We propose a novel approach that jointly removes reflection or transluce...
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Robust Face Recognition by Constrained Part-based Alignment
Developing a reliable and practical face recognition system is a long-st...
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Constructing a Non-Negative Low Rank and Sparse Graph with Data-Adaptive Features
This paper aims at constructing a good graph for discovering intrinsic d...
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PCANet: A Simple Deep Learning Baseline for Image Classification?
In this work, we propose a very simple deep learning network for image c...
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Sparse Illumination Learning and Transfer for Single-Sample Face Recognition with Image Corruption and Misalignment
Single-sample face recognition is one of the most challenging problems i...
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Blind Image Deblurring by Spectral Properties of Convolution Operators
In this paper, we study the problem of recovering a sharp version of a g...
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Sparsity and Robustness in Face Recognition
This report concerns the use of techniques for sparse signal representat...
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TILT: Transform Invariant Low-rank Textures
In this paper, we show how to efficiently and effectively extract a clas...
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Robust Recovery of Subspace Structures by Low-Rank Representation
In this work we address the subspace recovery problem. Given a set of da...
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Fast L1-Minimization Algorithms For Robust Face Recognition
L1-minimization refers to finding the minimum L1-norm solution to an und...
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Segmentation of Natural Images by Texture and Boundary Compression
We present a novel algorithm for segmentation of natural images that har...
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