62 citations · 114 across the 11 of their papers we have counts for
11 papers
CT: Counterfactual Causal Reasoning for Sentiment Shifts in Social-Media Conversation Trees
S M Rafiuddin, Atriya Sen
Sentiment in social-media threads does not only vary across posts; it shifts as users react to claims, corrections, evidence, and hostility within a branching reply tree. We study…
RAFP: Identifying LLM Lineages via Rare-Region Fingerprints
Yun-Yun Tsai, Jia Hao Liang, Chuan Guo +2
Large language models (LLMs) are increasingly released under restricted licenses, creating a growing need for robust model ownership verification. Existing fingerprinting methods a…
Guarantees of confidentiality via Hammersley-Chapman-Robbins bounds
Kamalika Chaudhuri, Chuan Guo, Laurens van der Maaten +2
Protecting privacy during inference with deep neural networks is possible by adding noise to the activations in the last layers prior to the final classifiers or other task-specifi…
GeoDE: a Geographically Diverse Evaluation Dataset for Object Recognition
Vikram V. Ramaswamy, Sing Yu Lin, Dora Zhao +4
Current dataset collection methods typically scrape large amounts of data from the web. While this technique is extremely scalable, data collected in this way tends to reinforce st…
Bounding Training Data Reconstruction in Private (Deep) Learning
Chuan Guo, Brian Karrer, Kamalika Chaudhuri +1
Differential privacy is widely accepted as the de facto method for preventing data leakage in ML, and conventional wisdom suggests that it offers strong protection against privacy…
CrypTen: Secure Multi-Party Computation Meets Machine Learning
Brian Knott, Shobha Venkataraman, Awni Hannun +3
Secure multi-party computation (MPC) allows parties to perform computations on data while keeping that data private. This capability has great potential for machine-learning applic…
Data Appraisal Without Data Sharing
Mimee Xu, Laurens van der Maaten, Awni Hannun
One of the most effective approaches to improving the performance of a machine learning model is to procure additional training data. A model owner seeking relevant training data f…
Secure multiparty computations in floating-point arithmetic
Chuan Guo, Awni Hannun, Brian Knott +3
Secure multiparty computations enable the distribution of so-called shares of sensitive data to multiple parties such that the multiple parties can effectively process the data whi…
Convolutional Networks with Dense Connectivity
Gao Huang, Zhuang Liu, Geoff Pleiss +2
Recent work has shown that convolutional networks can be substantially deeper, more accurate, and efficient to train if they contain shorter connections between layers close to the…
Certified Data Removal from Machine Learning Models
Chuan Guo, Tom Goldstein, Awni Hannun +1
Good data stewardship requires removal of data at the request of the data's owner. This raises the question if and how a trained machine-learning model, which implicitly stores inf…
Time Series Classification using the Hidden-Unit Logistic Model
Wenjie Pei, Hamdi Dibeklioğlu, David M. J. Tax +1
We present a new model for time series classification, called the hidden-unit logistic model, that uses binary stochastic hidden units to model latent structure in the data. The hi…