1 citations · 2 across the 10 of their papers we have counts for
14 papers
Correcting Burst Errors with Applications to DNA-Based Data Storage
Yuan-Pon Chen, Olgica Milenkovic
We introduce the problem of permutation burst error-correction, motivated by applications in molecular data storage with nanopore sequencing read platforms. A permutation burst of…
Transition Path Sampling Using Koopman Operators and Exit-Time Optimal Control
Boya Hou, Shane Wang, Siddharth Ambekar +2
Sampling transitions between metastable states is a central problem in dynamical systems theory and molecular dynamics in particular. A key challenge is the existence of high free-…
Correcting Contextual Deletions in DNA Nanopore Readouts
Yuan-Pon Chen, Olgica Milenkovic, João Ribeiro +1
The problem of designing codes for deletion-correction and synchronization has received renewed interest due to applications in DNA-based data storage systems that use nanopore seq…
Spatially-Coupled Network RNA Velocities: A Control-Theoretic Perspective
Boya Hou, Maxim Raginsky, Abhishek Pandey +1
RNA velocity is an important model that combines cellular spliced and unspliced RNA counts to infer dynamical properties of various regulatory functions. Despite its wide applicabi…
The Trojan Knowledge: Bypassing Commercial LLM Guardrails via Harmless Prompt Weaving and Adaptive Tree Search
Rongzhe Wei, Peizhi Niu, Xinjie Shen +7
Large language models (LLMs) remain vulnerable to jailbreak attacks that bypass safety guardrails to elicit harmful outputs. Existing approaches overwhelmingly operate within the p…
WaveletDiff: Multilevel Wavelet Diffusion For Time Series Generation
Yu-Hsiang Wang, Olgica Milenkovic
Time series are ubiquitous in many applications that involve forecasting, classification and causal inference tasks, such as healthcare, finance, audio signal processing and climat…
GUARD: Guided Unlearning and Retention via Data Attribution for Large Language Models
Peizhi Niu, Evelyn Ma, Huiting Zhou +5
Unlearning large language models (LLMs) is important due to copyright and privacy concerns. A key challenge is unintended forgetting, where removing data inadvertently impairs mode…
Do LLMs Really Forget? Evaluating Unlearning with Knowledge Correlation and Confidence Awareness
Rongzhe Wei, Peizhi Niu, Hans Hao-Hsun Hsu +9
Machine unlearning techniques aim to mitigate unintended memorization in large language models (LLMs). However, existing approaches predominantly focus on the explicit removal of i…
DNA Tails for Molecular Flash Memory
Jin Sima, Chao Pan, S. Kasra Tabatabaei +3
DNA-based data storage systems face practical challenges due to the high cost of DNA synthesis. A strategy to address the problem entails encoding data via topological modification…
DMol: A Highly Efficient and Chemical Motif-Preserving Molecule Generation Platform
Peizhi Niu, Yu-Hsiang Wang, Vishal Rana +3
We introduce a new graph diffusion model for small molecule generation, DMol, which outperforms the state-of-the-art DiGress model in terms of validity by roughly 1.5% across all b…
Generalized Orthogonal de Bruijn and Kautz Sequences
Yuan-Pon Chen, Jin Sima, Olgica Milenkovic
A de Bruijn sequence of order over a finite alphabet is a cyclic sequence with the property that it contains every possible -sequence as a substring exactly once. Orthogonal…
Reducing Data Fragmentation in Data Deduplication Systems via Partial Repetition and Coding
Yun-Han Li, Jin Sima, Ilan Shomorony +1
Data deduplication, one of the key features of modern Big Data storage devices, is the process of removing replicas of data chunks stored by different users. Despite the importance…
Federated Aggregation of Mallows Rankings: A Comparative Analysis of Borda and Lehmer Coding
Jin Sima, Vishal Rana, Olgica Milenkovic
Rank aggregation combines multiple ranked lists into a consensus ranking. In fields like biomedical data sharing, rankings may be distributed and require privacy. This motivates th…
Perturbation-Resilient Sets for Dynamic Service Balancing
Jin Sima, Chao Pan, Olgica Milenkovic
Balanced and swap-robust minimal trades, introduced in [1], are important for studying the balance and stability of server access request protocols under data popularity changes. C…