The Star

New finance chief vows to create optimal policy

Prudent approach: Purbaya sings the national anthem during the handover ceremony from his predecessor Sri Mulyani. All eyes are now on whether he can convince investors that he will maintain fiscal ...
Investopedia

Economic Order Quantity (EOQ): Key Insights for Efficient Inventory Management

Michael Boyle is an experienced financial professional with more than 10 years working with financial planning, derivatives, equities, fixed income, project management, and analytics. Economic order ...
IEEE

Policy-Adjustable Q-Learning for Data-Driven Nonlinear Optimal Tracking Control

Abstract: This article investigates a novel policy-adjustable Q-learning (PA-QL) algorithm aimed at addressing the optimal tracking control (OTC) problem for nonlinear discrete-time (DT) systems with ...
IEEE

Robust Reinforcement Learning via Leveraging Historically Optimal Policy With Regulation of Performance

Abstract: Most existing adversarial training methods in reinforcement learning (RL) offer limited robustness and remain vulnerable to novel attacks. To address this limitation, an approach that ...
GitHub

Near-optimal vector quantization for LLM KV cache compression.

Random rotation: Multiply the input vector by a fixed random orthogonal matrix. This makes each coordinate follow a known Beta(d/2, d/2) distribution. Lloyd-Max scalar quantization: Quantize each ...
GitHub

GitHub - Ryuketsukami/turboquant-compression: Near-optimal vector quantization for LLM KV cache compression. Python implementation of TurboQuant (ICLR 2026) — PolarQuant ...

Near-optimal vector quantization for LLM KV cache compression. Python implementation of TurboQuant (ICLR 2026) — PolarQuant + QJL for 3-bit quantization with minimal accuracy loss and up to 8x memory ...