SOTAVerified

Computational Efficiency

Methods and optimizations to reduce the computational resources (e.g., time, memory, or power) needed for training and inference in models. This involves techniques that streamline processing, optimize algorithms, or leverage hardware to enhance performance without compromising accuracy.

Papers

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 4701–4750 of 4891 papers

TitleStatusHype
The constrained Dantzig selector with enhanced consistency—0
Distributed Flexible Nonlinear Tensor Factorization—0
An improved chromosome formulation for genetic algorithms applied to variable selection with the inclusion of interaction terms—0
Online Human Action Detection using Joint Classification-Regression Recurrent Neural NetworksCode0
An Initial Seed Selection Algorithm for K-means Clustering of Georeferenced Data to Improve Replicability of Cluster Assignments for Mapping Application—0
Distribution-Free Predictive Inference For RegressionCode0
Online Nonnegative Matrix Factorization with Outliers—0
A Semi-Lagrangian two-level preconditioned Newton-Krylov solver for constrained diffeomorphic image registration—0
The deterministic information bottleneckCode0
An Empirical Study of Dimensional Reduction Techniques for Facial Action Units Detection—0
Scalable Bayesian Rule ListsCode0
Clustering with a Reject Option: Interactive Clustering as Bayesian Prior Elicitation—0
Depth-Based Object Tracking Using a Robust Gaussian FilterCode0
A Harmonic Extension Approach for Collaborative Ranking—0
Variational Hamiltonian Monte Carlo via Score Matching—0
Learning Minimum Volume Sets and Anomaly Detectors from KNN Graphs—0
The demodulated band transformCode0
Sub-Sampled Newton Methods II: Local Convergence Rates—0
Simple, Robust and Optimal Ranking from Pairwise Comparisons—0
Successive Ray Refinement and Its Application to Coordinate Descent for LASSO—0
Compressed Dynamic Mode Decomposition for Background Modeling—0
Hierarchical Sparse Modeling: A Choice of Two Group Lasso Formulations—0
A New Statistical Framework for Genetic Pleiotropic Analysis of High Dimensional Phenotype Data—0
Pan-Sharpening With a Hyper-Laplacian Penalty—0
Efficient Video Segmentation Using Parametric Graph Partitioning—0
Unsupervised Synchrony Discovery in Human Interaction—0
Incremental Truncated LSTD—0
Efficient Output Kernel Learning for Multiple Tasks—0
Fast clustering for scalable statistical analysis on structured images—0
Efficient Training of Very Deep Neural Networks for Supervised Hashing—0
Sequential Optimization for Efficient High-Quality Object Proposal Generation—0
Hierarchical Variational ModelsCode0
Symmetry-invariant optimization in deep networks—0
Understanding symmetries in deep networks—0
TiMEx: A Waiting Time Model for Mutually Exclusive Groups of Cancer Alterations—0
Robust Partially-Compressed Least-Squares—0
Fast and Accurate Poisson Denoising with Optimized Nonlinear Diffusion—0
Learning Summary Statistic for Approximate Bayesian Computation via Deep Neural Network—0
Fast Discrete Distribution Clustering Using Wasserstein Barycenter with Sparse SupportCode0
Learning Wake-Sleep Recurrent Attention Models—0
Projection Bank: From High-dimensional Data to Medium-length Binary Codes—0
Sensor Selection by Linear Programming—0
A tree-based kernel for graphs with continuous attributes—0
Vision-Based Road Detection using Contextual Blocks—0
Mining Combined Causes in Large Data Sets—0
Places205-VGGNet Models for Scene RecognitionCode0
Compact Convolutional Neural Network Cascade for Face DetectionCode0
DNA cyclization and looping in the wormlike limit: normal modes and the validity of the harmonic approximation—0
Real-time 2D/3D Registration via CNN Regression—0
High Performance Computing of Gene Regulatory Networks using a Message-Passing Model—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1ViTaLHamming Loss0.05—Unverified