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

Accelerating Stochastic Programs using GPU arrays: Sizing a grid-scale energy park

🔍 Explore curated resources on Reinforcement Learning with Verifiable Rewards (RLVR) and the reasoning limits of Large Language Models (LLMs).

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

HIV Data Simulation in Python (Master's Thesis Model)

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.

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.

🛠️ 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)

Using Bayesian optimization to design an optimal urban drainage network

Implementation of a few optimization algorithms

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.