Bin Gu

Faster On-Device Training Using New Federated Momentum Algorithm

2020 · arXiv (Cornell University)

Mobile crowdsensing has gained significant attention in recent years and has become a critical paradigm for emerging Internet of Things applications. The sensing devices continuously generate a significant quantity of data, which provide tremendous opportunities …

Improved Bilevel Model: Fast and Optimal Algorithm with Theoretical Guarantee

2020 · arXiv (Cornell University)

Due to the hierarchical structure of many machine learning problems, bilevel programming is becoming more and more important recently, however, the complicated correlation between the inner and outer problem makes it extremely challenging to solve. …

Fast and Scalable Adversarial Training of Kernel SVM via Doubly Stochastic Gradients

2021 · arXiv (Cornell University)

Adversarial attacks by generating examples which are almost indistinguishable from natural examples, pose a serious threat to learning models. Defending against adversarial attacks is a critical element for a reliable learning system. Support vector machine …

Robust Spoof Speech Detection Based on Multi-Scale Feature Aggregation and Dynamic Convolution

2024

Spoof speech detection (SSD) can help to protect an automatic speaker recognition system against malicious attacks. However, there exists a great diversity in the spoof utterances generated by different text-to-speech and voice conversion algorithms, resulting …