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20092023
most citedA Simple Unified Framework for Detecting Out-of-Distribution Samples and Adversarial Attacks

982 citations · 2.8k across the 131 of their papers we have counts for

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Showing 2018Show all

7 papers · 1 filter

eess.SY2018

Simulation-based Distributed Coordination Maximization over Networks

Hyeryung Jang, Jinwoo Shin, Yung Yi

In various online/offline multi-agent networked environments, it is very popular that the system can benefit from coordinating actions of two interacting agents at some cost of coo…

cs.LG2018★ 12 cited

Anytime Neural Prediction via Slicing Networks Vertically

Hankook Lee, Jinwoo Shin

The pioneer deep neural networks (DNNs) have emerged to be deeper or wider for improving their accuracy in various applications of artificial intelligence. However, DNNs are often…

stat.ML2018★ 982 cited

A Simple Unified Framework for Detecting Out-of-Distribution Samples and Adversarial Attacks

Kimin Lee, Kibok Lee, Honglak Lee +1

Detecting test samples drawn sufficiently far away from the training distribution statistically or adversarially is a fundamental requirement for deploying a good classifier in man…

cs.CV2018

Hierarchical Novelty Detection for Visual Object Recognition

Kibok Lee, Kimin Lee, Kyle Min +3

Deep neural networks have achieved impressive success in large-scale visual object recognition tasks with a predefined set of classes. However, recognizing objects of novel classes…

stat.ML2018★ 2 cited

Gauged Mini-Bucket Elimination for Approximate Inference

Sungsoo Ahn, Michael Chertkov, Jinwoo Shin +1

Computing the partition function of a discrete graphical model is a fundamental inference challenge. Since this is computationally intractable, variational approximations are o…

cs.LG2018★ 4 cited

Stochastic Chebyshev Gradient Descent for Spectral Optimization

Insu Han, Haim Avron, Jinwoo Shin

A large class of machine learning techniques requires the solution of optimization problems involving spectral functions of parametric matrices, e.g. log-determinant and nuclear no…