10 papers
Stochastic Saddle Avoidance Beyond Unit Excitation and Smoothness: A Pathwise Lyapunov-Perron Framework
Junwen Qiu, Bohao Ma, Andre Milzarek +1
Unit excitation (UE) is a common assumption in stochastic saddle avoidance: the stochastic error must have a uniformly positive component along every direction, in expectation. Thi…
FlexiSLM: A Spoken Language Model with Dynamic and Controllable Frame Rates
Jiaqi Li, Chaoren Wang, Xiaohai Tian +9
Spoken language models (SLMs) extend LLMs to speech input and output. Existing SLMs represent speech at fixed frame rates (e.g., 25 or 12.5 Hz), ignoring the time-varying informati…
Random Reshuffling with Momentum: Complexity Bounds and Last-iterate Convergence
Junwen Qiu, Bohao Ma, Andre Milzarek
Random reshuffling with momentum (RRM) corresponds to the SGD optimizer with the 'momentum' option enabled, as found in many machine learning libraries such as PyTorch and TensorFl…
Zero-VC: Zero-Lookahead Streaming Voice Conversion via Speaker Anonymization
Yudong Li, Zihao Fang, Junwen Qiu +4
Streaming zero-shot voice conversion struggles to disentangle timbre from linguistic content without degrading utility or inflating latency. Current methods rely on information bot…
Shuffling the Stochastic Mirror Descent via Dual Lipschitz Continuity and Kernel Conditioning
Junwen Qiu, Leilei Mei, Junyu Zhang
The global Lipschitz smoothness condition underlies most convergence and complexity analyses via two key consequences: the descent lemma and the gradient Lipschitz continuity. How…
A New Kernel Regularity Condition for Distributed Mirror Descent: Broader Coverage and Simpler Analysis
Junwen Qiu, Ziyang Zeng, Leilei Mei +1
Existing convergence of distributed optimization methods in non-Euclidean geometries typically rely on kernel assumptions: (i) global Lipschitz smoothness and (ii) bi-convexity of…