18 citations · 68 across the 14 of their papers we have counts for
5 papers · 1 filter
ACon: Adaptive Conformal Consensus for Provable Blockchain Oracles
Sangdon Park, Osbert Bastani, Taesoo Kim
Blockchains with smart contracts are distributed ledger systems that achieve block-state consistency among distributed nodes by only allowing deterministic operations of smart cont…
Ruby: Unmasking Unsafe Rust in Stripped Binaries via Machine Learning
Xiang Cheng, Sangdon Park, HyungSeok Han +2
Rust, as an emerging system programming language, introduces to allow developers to bypass safety checks during compilation. As a result, memory safety bugs are t…
PAC Prediction Sets for Meta-Learning
Sangdon Park, Edgar Dobriban, Insup Lee +1
Uncertainty quantification is a key component of machine learning models targeted at safety-critical systems such as in healthcare or autonomous vehicles. We study this problem in…
Towards PAC Multi-Object Detection and Tracking
Shuo Li, Sangdon Park, Xiayan Ji +2
Accurately detecting and tracking multi-objects is important for safety-critical applications such as autonomous navigation. However, it remains challenging to provide guarantees o…
iDECODe: In-distribution Equivariance for Conformal Out-of-distribution Detection
Ramneet Kaur, Susmit Jha, Anirban Roy +4
Machine learning methods such as deep neural networks (DNNs), despite their success across different domains, are known to often generate incorrect predictions with high confidence…