Algorithms
Publication
Orthogonal Random Forest for Causal Inference
Video
On The Hardness of Reinforcement Learning With Value-Function Approximation (and The Lack of Understanding Thereof)
Value-function approximation methods that operate in batch mode have foundational importance to reinforcement learning (RL). Finite sample guarantees for these methods—which provide the theoretical backbones for empirical (“deep”) RL today—crucially rely on strong representation assumptions,…
Tool
SeeDot
SeeDot is an automatic quantization tool that generates efficient machine learning (ML) inference code for IoT devices. ML models are usually expressed in floating-point, and IoT devices typically lack hardware support for floating-point arithmetic. Hence,…