7 accepted papers
In Federated Learning (FL) the data in each client is typically assumed fixed or static. However data often comes in an incremental manner in real-world applications where the data domain may increase dynamically. In this work we study catastrophic forgetting with data heterogeneity in Federated Inc…
In critical environments that require a high accuracy of decisions, utilizing human cognitive strengths and expertise in addition to machine observations is advantageous to improve decision quality and enhance situational awareness. While the current literature on human decision making is primarily…
The first provably efficient algorithm for learning graph neural networks (GNNs) with one hidden layer for node information convolution is provided in this paper. Two types of GNNs are investigated, depending on whether labels are attached to nodes or graphs. A comprehensive framework for designing…
In this paper, we present a statistical mechanics framework to understand the effect of sampling properties of training data on the generalization gap of machine learning (ML) algorithms. We connect the generalization gap to the spatial properties of a sample design characterized by the pair correla…
The problem of quickest change detection (QCD) in anonymous heterogeneous sensor networks is studied. There are n heterogeneous sensors and a fusion center. The sensors are clustered into K groups, and different groups follow different data generating distributions. At some unknown time, an event oc…
We explore the design of an effective crowdsourcing system for an M -ary classification task. Crowd workers complete simple binary microtasks whose results are aggregated to give the final decision. We consider the scenario where the workers have a reject option so that they are allowed to skip micr…
In this work, we investigate the accelerated proximal gradient method for nonconvex programming (APGnc). The method compares between a usual proximal gradient step and a linear extrapolation step, and accepts the one that has a lower function value to achieve a monotonic decrease. In specific, under…