Kuaishou Tech
Kuaishou Tech
Dec 18, 2025 · Artificial Intelligence

How SSR Turns Multimodal Recommendation into an Interpretable Frequency‑Domain Reasoning Problem

The paper introduces SSR, a novel multimodal recommendation framework that leverages graph Fourier transforms, energy‑balanced frequency bands, structured regularization, and low‑rank tensor decomposition to replace black‑box fusion with explainable, adaptive reasoning, achieving state‑of‑the‑art results on Amazon datasets and strong cold‑start performance.

cold startcontrastive learningfrequency domain
0 likes · 15 min read
How SSR Turns Multimodal Recommendation into an Interpretable Frequency‑Domain Reasoning Problem
Data Party THU
Data Party THU
Nov 22, 2025 · Artificial Intelligence

How Frequency‑Refined Augmentation Boosts Contrastive Learning for Time‑Series Classification

FreRA introduces a lightweight, plug‑in frequency‑refined augmentation that adaptively refines spectral components to preserve global semantics while injecting variance, dramatically improving contrastive learning performance on time‑series classification, anomaly detection, and transfer learning across multiple benchmark datasets.

Data Augmentationcontrastive learningfrequency domain
0 likes · 13 min read
How Frequency‑Refined Augmentation Boosts Contrastive Learning for Time‑Series Classification
Alibaba Cloud Developer
Alibaba Cloud Developer
Mar 10, 2020 · Artificial Intelligence

Can Frequency‑Domain Learning Boost Image Inference Efficiency?

This article presents a system‑level approach that performs deep‑learning inference directly on JPEG frequency components, uses a gating mechanism to select important DCT coefficients, and demonstrates higher accuracy with far lower bandwidth for image classification and instance segmentation tasks.

Bandwidth Reductioncomputer visiondeep learning
0 likes · 22 min read
Can Frequency‑Domain Learning Boost Image Inference Efficiency?