5 papers
Optimization Dynamics Imprint Semantic Specificity in Contrastive Embedding Norms
Ziwei Su, Junyu Ren, Victor Veitch
Contrastive embedding models trained with scale-invariant losses are typically paired with distance metrics like cosine similarity, effectively ignoring embedding magnitudes. Howev…
Model-based Bootstrap of Controlled Markov Chains
Ziwei Su, Imon Banerjee, Diego Klabjan
We propose and analyze a model-based bootstrap for transition kernels in finite controlled Markov chains (CMCs) with possibly nonstationary or history-dependent control policies, a…
Overcoming the Incentive Collapse Paradox
Qichuan Yin, Ziwei Su, Shuangning Li
AI-assisted task delegation is increasingly common, yet human effort in such systems is costly and typically unobserved. Recent work by Bastani and Cachon (2025); Sambasivan et al.…
Central Limit Theorems for Transition Probabilities of Controlled Markov Chains
Ziwei Su, Imon Banerjee, Diego Klabjan
We develop a central limit theorem (CLT) for a non-parametric estimator of the transition matrices in controlled Markov chains (CMCs) with finite state-action spaces. Our results e…
Differentiable Calibration of Inexact Stochastic Simulation Models via Kernel Score Minimization
Ziwei Su, Diego Klabjan
Stochastic simulation models are generative models that mimic complex systems to help with decision-making. The reliability of these models heavily depends on well-calibrated input…