15 citations · 75 across the 31 of their papers we have counts for
10 papers · 1 filter
Online MAP Inference and Learning for Nonsymmetric Determinantal Point Processes
Aravind Reddy, Ryan A. Rossi, Zhao Song +6
In this paper, we introduce the online and streaming MAP inference and learning problems for Non-symmetric Determinantal Point Processes (NDPPs) where data points arrive in an arbi…
Exact Representation of Sparse Networks with Symmetric Nonnegative Embeddings
Sudhanshu Chanpuriya, Ryan A. Rossi, Anup Rao +4
Many models for undirected graphs are based on factorizing the graph's adjacency matrix; these models find a vector representation of each node such that the predicted probability…
Customs Fraud Detection in the Presence of Concept Drift
Tung-Duong Mai, Kien Hoang, Aitolkyn Baigutanova +2
Capturing the changing trade pattern is critical in customs fraud detection. As new goods are imported and novel frauds arise, a drift-aware fraud detection system is needed to det…
Optimal Space and Time for Streaming Pattern Matching
Tung Mai, Anup Rao, Ryan A. Rossi +1
In this work, we study longest common substring, pattern matching, and wildcard pattern matching in the asymmetric streaming model. In this streaming model, we have random access t…
Coresets for Classification -- Simplified and Strengthened
Tung Mai, Anup B. Rao, Cameron Musco
We give relative error coresets for training linear classifiers with a broad class of loss functions, including the logistic loss and hinge loss. Our construction achieves $(1\pm ε…
Responses to COVID-19 with Probabilistic Programming
Assem Zhunis, Tung-Duong Mai, Sundong Kim
The COVID-19 pandemic left its unique mark on the 21st century as one of the most significant disasters in history, triggering governments all over the world to respond with a wide…
Asymptotics of Ridge Regression in Convolutional Models
Mojtaba Sahraee-Ardakan, Tung Mai, Anup Rao +3
Understanding generalization and estimation error of estimators for simple models such as linear and generalized linear models has attracted a lot of attention recently. This is in…
Machine Unlearning via Algorithmic Stability
Enayat Ullah, Tung Mai, Anup Rao +2
We study the problem of machine unlearning and identify a notion of algorithmic stability, Total Variation (TV) stability, which we argue, is suitable for the goal of exact unlearn…
Online Discrepancy Minimization via Persistent Self-Balancing Walks
David Arbour, Drew Dimmery, Tung Mai +1
We study the online discrepancy minimization problem for vectors in in the oblivious setting where an adversary is allowed fix the vectors in…
Fundamental Tradeoffs in Distributionally Adversarial Training
Mohammad Mehrabi, Adel Javanmard, Ryan A. Rossi +2
Adversarial training is among the most effective techniques to improve the robustness of models against adversarial perturbations. However, the full effect of this approach on mode…