Paper Review: DeltaLag – An End‑to‑End Deep Learning Framework for Dynamically Learning Lead‑Lag Patterns in Financial Markets

DeltaLag introduces a sparse cross‑attention mechanism that dynamically discovers pair‑specific, time‑varying lead‑lag relationships in US equity markets and uses them to construct interpretable trading signals, achieving significantly higher annualized returns, Sharpe ratios, and information coefficients than fixed‑lag, statistical, and other spatio‑temporal deep learning baselines.

Deep LearningDeltaLagfinancial time series

0 likes · 13 min read

Paper Review: DeltaLag – An End‑to‑End Deep Learning Framework for Dynamically Learning Lead‑Lag Patterns in Financial Markets

Tencent Advertising Technology

Aug 27, 2024 · Artificial Intelligence

Auxiliary Ranking Loss Enhances Classification Ability in Sparse‑Feedback CTR Prediction

This study investigates how adding an auxiliary ranking loss to click‑through‑rate (CTR) models not only improves ranking but also alleviates gradient‑vanishing for negative samples, thereby boosting the primary classification performance, especially under sparse positive‑feedback conditions.

AdvertisingCTR predictiongradient analysis

0 likes · 13 min read

Auxiliary Ranking Loss Enhances Classification Ability in Sparse‑Feedback CTR Prediction

NetEase Media Technology Team

Jul 12, 2019 · Artificial Intelligence

Video Highlight Detection and GIF Cover Generation Using 3D Convolutional Scoring

The paper proposes a 3D‑CNN scoring system that ranks short, information‑dense video segments, selects the most exciting one, and converts it into a looping GIF cover, replacing static thumbnails; trained on large video‑GIF datasets with pairwise ranking loss, it improves click‑through rates while reducing bad‑case generation.

3D CNNGIF generationVideo Summarization

0 likes · 13 min read

Video Highlight Detection and GIF Cover Generation Using 3D Convolutional Scoring