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A list of all the posts and pages found on the site. For you robots out there, there is an XML version available for digesting as well.
Pages
Posts
Solution to CLRS Problem 16-2 (Scheduling to Minimize Average Completion Time)
Published:
This post provides a comprehensive solution for Problem 16-2 from Introduction to Algorithms (CLRS), focusing on the Single-Machine Scheduling problem.
Solution to CLRS Problem 16-1 (Coin Changing Problem)
Published:
This post provides a detailed solution and analysis for Problem 16-1 (Coin Changing) from Introduction to Algorithms (CLRS). It discusses the conditions under which the greedy algorithm yields an optimal solution and when dynamic programming is required.
OS Lab 4: Scheduling in xv6 (Round-Robin & Priority)
Published:
This post documents Lab 4 of the Operating Systems course, focusing on the scheduling mechanisms in the xv6 kernel.
Solution to CLRS Problem 17-2 (Making Binary Search Dynamic)
Published:
This post explores the solution for Problem 17-2 from Introduction to Algorithms (CLRS).
Solution to CLRS Problem 17-4-3 (Amortized Analysis of Dynamic Tables)
Published:
This post presents the solution for Problem 17-4-3 in Introduction to Algorithms (CLRS).
portfolio
publications
Pose-Motion Video Anomaly Detection via Memory-Augmented Reconstruction and Conditional Variational Prediction
Weilin Wan, Weizhong Zhang, Cheng Jin
Published in ICME, 2023
This paper presents a skeleton-based video anomaly detection framework (PoMo) that combines memory-augmented pose reconstruction and conditional variational motion prediction to effectively identify spatial and temporal anomalies.
Out-of-distribution detection using neural activation prior
Weilin Wan, Weizhong Zhang, Quan Zhou, Fan Yi, Cheng Jin
arXiv preprint arXiv:2402.18162, 2024
This paper introduces Neural Activation Prior (NAP), a parameter-free post-hoc framework that effectively detects out-of-distribution samples by exploiting the distinct “signal-to-noise” activation patterns within feature channels without requiring retraining.
Computational Budget Should Be Considered in Data Selection
Weilin Wan, Weizhong Zhang, Cheng Jin
Published in NeurIPS, 2025
This paper challenges the assumption that data importance is budget-independent and proposes CADS, a computation-aware data selection framework that dynamically optimizes training subsets under explicit computational constraints.
Advanced Black-Box Tuning of Large Language Models with Limited API Calls
Zhikang Xie, Weilin Wan, Peizhu Gong, Weizhong Zhang, Cheng Jin
Published in AAAI, 2026
This paper proposes Advanced Black-Box Tuning (ABBT), a framework that reduces API calls by an order of magnitude in LLM optimization through instruction-aware initialization and Langevin dynamics-based evolution.
Explore and Establish Synergistic Effects Between Weight Pruning and Coreset Selection in Neural Network Training
Weilin Wan, Fan Yi, Weizhong Zhang, Quan Zhou, Cheng Jin
Published in AAAI, 2026
This paper investigates the interplay between weight pruning and coreset selection, proposing a synergistic training mechanism (SWaST) that alternately optimizes both to improve efficiency and accuracy while preventing critical information loss.
Holistic Scaling Laws for Optimal Mixture-of-Experts Architecture Optimization
Weilin Wan, Jingtao Han, Weizhong Zhang, Cheng Jin
arXiv preprint arXiv:2603.21862, 2026
This paper establishes the first holistic framework for global MoE architectural optimization, reducing the intractable 16-dimensional search space to a two-phase sequential procedure via mathematical constraints and rank-preserving properties.
talks
teaching
Introduction to Computer Systems (ICS), AIE210006.01
Undergraduate course, Fudan University, College of Computer Science and Artificial Intelligence, 2024
This course provides an introduction to the internal operation of modern computer systems, covering topics such as data representation, assembly language, memory hierarchy, linking, and exceptional control flow.