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Count-Min Sketch

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Alibaba International Intelligent Technology

Sep 18, 2026 · Artificial Intelligence

UTTSI: Test-Time Selective Inference Boosts CTR Prediction Without Retraining

Alibaba researchers propose UTTSI, a training-free, model-agnostic framework that estimates per-sample uncertainty at inference time using frequency priors and gradient-based attribution, then adaptively allocates compute — filtering noisy features and exploring multiple inference paths only for uncertain samples — achieving a 5.3% CTR lift in a 7-day online A/B test with just 2.8× average model calls.

CIKM 2026CTR predictionCount-Min Sketch

0 likes · 12 min read

UTTSI: Test-Time Selective Inference Boosts CTR Prediction Without Retraining

JD Tech

Feb 19, 2025 · Backend Development

Understanding the Design and Implementation of Caffeine Cache

This article provides a comprehensive walkthrough of Caffeine cache's architecture, explaining its fixed-size eviction policy, underlying data structures such as ConcurrentHashMap, MPSC buffers, Count‑Min Sketch frequency tracking, and the dynamic window‑probation‑protected zones, while detailing key methods like put, getIfPresent, and maintenance.

CaffeineCount-Min Sketchcache

0 likes · 71 min read

Understanding the Design and Implementation of Caffeine Cache

NetEase Yanxuan Technology Product Team

Jul 25, 2022 · Big Data

Probability Algorithms in Big Data: BloomFilter and Count-min Sketch Applications

The article explains how space‑efficient probabilistic structures such as BloomFilter and Count‑min Sketch enable large‑scale data deduplication, join pruning, real‑time idempotent filtering, and approximate top‑K analytics by trading modest accuracy loss for dramatically reduced storage and faster computation.

BloomFilterCount-Min SketchJOIN optimization

0 likes · 12 min read

Probability Algorithms in Big Data: BloomFilter and Count-min Sketch Applications