conftrace_

Optimization & Theory

36,874 papers (3 classified directly here)

Subtopics

Optimization (14,983) Bayesian Inference (5,566) Learning Theory (5,334) Theory (4,955) Statistical Learning (4,117) Neural Network Optimization (3,649) Stochastic Processes (2,667) Loss Functions (1,162) Distributed Learning (1,135) Stochastic Methods (1,118) Online Algorithms (806) Statistics (684) Information Theory (318) Generalization (220) Sparse Optimization (158) Sample Complexity (99) Game Theory (30) Robust Optimization (17) Optimal Transport (14) Approximation Algorithms (10) Distributed Optimization (8) Convex Optimization (8)

Papers per year

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Papers (including subtopics)

A Causal And-Or Graph Model for Visibility Fluent Reasoning in Tracking Interacting Objects CVPR 2018
Wing Loss for Robust Facial Landmark Localisation With Convolutional Neural Networks CVPR 2018
Deep Regression Forests for Age Estimation CVPR 2018
Practical Block-Wise Neural Network Architecture Generation CVPR 2018
Deformation Aware Image Compression CVPR 2018
Distributable Consistent Multi-Object Matching CVPR 2018
Dynamic Scene Deblurring Using Spatially Variant Recurrent Neural Networks CVPR 2018
CodeSLAM — Learning a Compact, Optimisable Representation for Dense Visual SLAM CVPR 2018
SobolevFusion: 3D Reconstruction of Scenes Undergoing Free Non-Rigid Motion CVPR 2018
LDMNet: Low Dimensional Manifold Regularized Neural Networks CVPR 2018
Estimation of Camera Locations in Highly Corrupted Scenarios: All About That Base, No Shape Trouble CVPR 2018
Probabilistic Plant Modeling via Multi-View Image-to-Image Translation CVPR 2018
Camera Pose Estimation With Unknown Principal Point CVPR 2018
Inverse Composition Discriminative Optimization for Point Cloud Registration CVPR 2018
PiCANet: Learning Pixel-Wise Contextual Attention for Saliency Detection CVPR 2018
Curve Reconstruction via the Global Statistics of Natural Curves CVPR 2018
Beyond the Pixel-Wise Loss for Topology-Aware Delineation CVPR 2018
Learning to See in the Dark CVPR 2018
BPGrad: Towards Global Optimality in Deep Learning via Branch and Pruning CVPR 2018
A Biresolution Spectral Framework for Product Quantization CVPR 2018
Lightweight Probabilistic Deep Networks CVPR 2018
Sliced Wasserstein Distance for Learning Gaussian Mixture Models CVPR 2018
Local and Global Optimization Techniques in Graph-Based Clustering CVPR 2018
Learning Time/Memory-Efficient Deep Architectures With Budgeted Super Networks CVPR 2018
Anticipating Traffic Accidents With Adaptive Loss and Large-Scale Incident DB CVPR 2018