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Alimama Tech
Alimama Tech
Sep 8, 2021 · Artificial Intelligence

Deep Uncertainty-Aware Learning (DUAL) for Click‑Through Rate Prediction and Exploration Strategies

The paper presents Deep Uncertainty‑Aware Learning (DUAL), a scalable Bayesian deep‑learning framework that combines a neural feature extractor with a Gaussian‑process prior to model CTR prediction uncertainty, mitigates feedback‑loop bias, and enables confidence‑driven exploration (UCB and Thompson sampling) that improves long‑term utility while preserving accuracy.

CTR predictionContextual BanditsGaussian Process
0 likes · 15 min read
Deep Uncertainty-Aware Learning (DUAL) for Click‑Through Rate Prediction and Exploration Strategies
Efficient Ops
Efficient Ops
Jul 17, 2021 · Databases

How AutoTiKV’s Machine Learning Optimizes Beaver Search Engine Performance

This article describes how the Beaver search engine’s many performance‑related configuration parameters can be automatically tuned using machine‑learning techniques from OtterTune and AutoTiKV, detailing the background research, Gaussian Process regression model, Bayesian optimization process, implementation steps, test results, and future improvements.

Bayesian OptimizationBeaverDatabase Performance
0 likes · 23 min read
How AutoTiKV’s Machine Learning Optimizes Beaver Search Engine Performance