Resources of our survey paper "Enabling AI on Edges: Techniques, Applications and Challenges"
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Updated
May 17, 2024
Resources of our survey paper "Enabling AI on Edges: Techniques, Applications and Challenges"
RLeXplore provides stable baselines of exploration methods in reinforcement learning, such as intrinsic curiosity module (ICM), random network distillation (RND) and rewarding impact-driven exploration (RIDE).
Official code for our ECCV'22 paper "A Fast Knowledge Distillation Framework for Visual Recognition"
Sorting a stacks in a very very hard way.
Library Index - Data structures and search algorithms efficiency analysis
Fluid flow simulator using MFEM and multiscale space-time sub-domains.
Efficiently retireving the Sub_Array with Max value from an array.
Computationally efficient rolling window iterators for Python
Smart API for Crypto File Management.
The goal of this project was to develop a dictionary which is to be used in a spell checker. The spell checker will help users identify and correct misspelled words by comparing input words against the dictionary.
Represents a data structure that combines the characteristics of a priority queue and a key-value map. Elements are associated with priorities, allowing efficient retrieval, update, and removal based on priority.
efficient csv splitting
If you are a newbie in coding and wanna do CP then first solve this DSA question then move to cp..it will surely gonna help u clear the concepts. and get better at cp.
Source Code for 'Efficient Discrete Clustering with Anchor Graph (T-NNLS)'
[TIP] APP-Net: Auxiliary-point-based Push and Pull Operations for Efficient Point Cloud Recognition
This repo contains all the scripts that I wrote while working for various organisations as well as while contributing to open source projects
A teacher model with minimal bias or calibrate its outputs to reduce bias transfer during distillation. Focus on distilling information from teacher features that are less prone to bias, like semantic representations instead of raw activations.
VieCut 1.00 - Shared-memory Minimum Cuts
Custom cache object that clears the least-recently-used items.
This Bloom Filter implementation offers probabilistic data structure for fast set membership testing. Efficiently handling large datasets with minimal space, it ensures quick and accurate element existence checks, limits memory usage and retains speed.
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