Search Results for author:
Found 9 papers, 2 papers with code
CTAP for Chinese:A Linguistic Complexity Feature Automatic Calculation Platform
The construct of linguistic complexity has been widely used in language learning research.
Unifying Lane-Level Traffic Prediction from a Graph Structural Perspective: Benchmark and Baseline
Traffic prediction has long been a focal and pivotal area in research, witnessing both significant strides from city-level to road-level predictions in recent years.
A Bargaining-based Approach for Feature Trading in Vertical Federated Learning
We analyze the proposed bargaining model under perfect and imperfect performance information settings, proving the existence of an equilibrium that optimizes the parties' objectives.
An Auction-based Marketplace for Model Trading in Federated Learning
This FL market allows clients to gain monetary reward by selling their own models and improve local model performance through the purchase of others' models.
Technical Report: On the Convergence of Gossip Learning in the Presence of Node Inaccessibility
In this paper, we formulate and investigate the impact of inaccessible nodes to GL under a dynamic network topology.
TopCoW: Benchmarking Topology-Aware Anatomical Segmentation of the Circle of Willis (CoW) for CTA and MRA
The TopCoW dataset was the first public dataset with voxel-level annotations for thirteen possible CoW vessel components, enabled by virtual-reality (VR) technology.
RecUP-FL: Reconciling Utility and Privacy in Federated Learning via User-configurable Privacy Defense
In this paper, we seek to reconcile utility and privacy in FL by proposing a user-configurable privacy defense, RecUP-FL, that can better focus on the user-specified sensitive attributes while obtaining significant improvements in utility over traditional defenses.
Historical Inertia: A Neglected but Powerful Baseline for Long Sequence Time-series Forecasting
Long sequence time-series forecasting (LSTF) has become increasingly popular for its wide range of applications.
Prognostication of chronic disorders of consciousness using brain functional networks and clinical characteristics
Disorders of consciousness are a heterogeneous mixture of different diseases or injuries.
Neurons and Cognition
