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 3361–3370 of 4891 papers

TitleStatusHype
Data Association Aware POMDP Planning with Hypothesis Pruning Performance Guarantees—0
Switched Lyapunov Function based Controller Synthesis for Networked Control Systems: A Computationally Inexpensive Approach—0
The Virtues of Laziness in Model-based RL: A Unified Objective and AlgorithmsCode0
Efficient Explorative Key-term Selection Strategies for Conversational Contextual BanditsCode0
U-Statistics for Importance-Weighted Variational Inference—0
A Reinforcement Learning Approach for Scheduling Problems With Improved Generalization Through Order Swapping—0
Suitability of Quantized DEVS LIM Methods for Simulation of Power Systems—0
Direct Estimation of Parameters in ODE Models Using WENDy: Weak-form Estimation of Nonlinear DynamicsCode0
Efficient Ensemble for Multimodal Punctuation Restoration using Time-Delay Neural NetworkCode0
VIPeR: Provably Efficient Algorithm for Offline RL with Neural Function ApproximationCode0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1ViTaLHamming Loss0.05—Unverified