4 papers
COMPASS: Complete Multimodal Fusion via Proxy Tokens and Shared Spaces for Ubiquitous Sensing
Hao Wang, Yanyu Qian, Pengcheng Weng +4
Missing modalities in multimodal sensing cause not only information loss but also a fusion-interface mismatch: a fusion head trained on a canonical set of modality slots must opera…
Diverse via bounded Agreement: Geometric Regularization for Multimodal Fusion
Zixuan Xia, Hao Wang, Pengcheng Weng +4
Multimodal fusion is often treated as an optimization-balancing problem, where training signals are adjusted to prevent one modality from dominating the others. However, balanced o…
K-Score: Kalman Filter as a Principled Alternative to Reward Normalization in Reinforcement Learning
Zixuan Xia, Quanxi Li
We propose a simple yet effective alternative to reward normalization in policy gradient reinforcement learning by integrating a 1D Kalman filter for online reward estimation. Inst…
KOALA++: Efficient Kalman-Based Optimization with Gradient-Covariance Products
Zixuan Xia, Aram Davtyan, Paolo Favaro
We propose KOALA++, a scalable Kalman-based optimization algorithm that explicitly models structured gradient uncertainty in neural network training. Unlike second-order methods, w…