A summary of code optimization techniques and methods
- Updated
Aug 20, 2019
A summary of code optimization techniques and methods
Boost Valheim's FPS to forge a smoother Viking journey!
Learn the ins and outs of efficiently serving Large Language Models (LLMs). Dive into optimization techniques, including KV caching and Low Rank Adapters (LoRA), and gain hands-on experience with Predibase’s LoRAX framework inference server.
Primal-Dual algorithm for smooth regularization of non-smooth optimization functions
🔍 Explore curated resources on Reinforcement Learning with Verifiable Rewards (RLVR) and the reasoning limits of Large Language Models (LLMs).
Accelerating Stochastic Programs using GPU arrays: Sizing a grid-scale energy park
Optimization Techniques Lab (MA39207)
A collection of optimization methods in engineering applications (OMEA), implemented in Python — including linear, nonlinear and constrained, with examples.
This repository contains the implementation of a Part-of-Speech (POS) tagging system using Hidden Markov Models (HMMs) along with various decoding techniques and adversarial training strategies for sequence labeling tasks. Project for course DSCI 599 - Optimization Techniques for Data Science, Fall 2023
This repository contains my solutions to various problems from Codeforces contests, aimed at improving problem-solving skills in competitive programming. Each submission is stored with detailed information, including contest IDs and problem names, making it easy to track progress and learn from past solutions.
This repository contains my solutions to various Codeforces contest problems, showcasing problem-solving skills in competitive programming. Each submission includes contest IDs, problem names, solution timestamps, and a performance analysis on execution speed and memory usage.
HIV Data Simulation in Python (Master's Thesis Model)
🛠️ Explore large language models through hands-on projects and tutorials to enhance your understanding and practical skills in natural language processing.
HIV Data Simulation in R (Master's Thesis Model)
Implementation of a few optimization algorithms
Using Bayesian optimization to design an optimal urban drainage network
in-depth analysis and comparison of eight leading in-memory subgraph matching algorithms, QuickSI, GraphQL, CFL, CECI, DP-iso, RI, and VF2++.
All codes related to Optimization Techniques using Matlab
This repository contains Python implementations of the Simulated Annealing optimization algorithm. It includes two Colab notebooks — one that evaluates Simulated Annealing across 55 benchmark functions and another that focuses on a single test function (Ackley) — along with sample result files and documentation.
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