Search Results for author:
Found 7 papers, 3 papers with code
HPL-ESS: Hybrid Pseudo-Labeling for Unsupervised Event-based Semantic Segmentation
In this paper, we propose a novel hybrid pseudo-labeling framework for unsupervised event-based semantic segmentation, HPL-ESS, to alleviate the influence of noisy pseudo labels.
FairSync: Ensuring Amortized Group Exposure in Distributed Recommendation Retrieval
Specifically, FairSync resolves the issue by moving it to the dual space, where a central node aggregates historical fairness data into a vector and distributes it to all servers.
Mutual Information Maximization for Robust Plannable Representations
The later, while they present low sample complexity, they learn latent spaces that need to reconstruct every single detail of the scene.
REFIT: A Unified Watermark Removal Framework For Deep Learning Systems With Limited Data
The experimental results demonstrate that our fine-tuning based watermark removal attacks could pose real threats to the copyright of pre-trained models, and thus highlight the importance of further investigating the watermarking problem and proposing more robust watermark embedding schemes against the attacks.
Goal-conditioned Imitation Learning
Designing rewards for Reinforcement Learning (RL) is challenging because it needs to convey the desired task, be efficient to optimize, and be easy to compute.
Equitability of Dependence Measure
Measuring dependence between two random variables is very important, and critical in many applied areas such as variable selection, brain network analysis.
Dependence Measure for non-additive model
We proposed a new statistical dependency measure called Copula Dependency Coefficient(CDC) for two sets of variables based on copula.
