1 citations · 2 across the 8 of their papers we have counts for
5 papers · 1 filter
Learning to Jump: Thinning and Thickening Latent Counts for Generative Modeling
Tianqi Chen, Mingyuan Zhou
Learning to denoise has emerged as a prominent paradigm to design state-of-the-art deep generative models for natural images. How to use it to model the distributions of both conti…
SONAR: Joint Architecture and System Optimization Search
Elias Jääsaari, Michelle Ma, Ameet Talwalkar +1
There is a growing need to deploy machine learning for different tasks on a wide array of new hardware platforms. Such deployment scenarios require tackling multiple challenges, in…
Deep Adversarially-Enhanced k-Nearest Neighbors
Ren Wang, Tianqi Chen, Alfred Hero
Recent works have theoretically and empirically shown that deep neural networks (DNNs) have an inherent vulnerability to small perturbations. Applying the Deep k-Nearest Neighbors…
ASK: Adversarial Soft k-Nearest Neighbor Attack and Defense
Ren Wang, Tianqi Chen, Philip Yao +3
K-Nearest Neighbor (kNN)-based deep learning methods have been applied to many applications due to their simplicity and geometric interpretability. However, the robustness of kNN-b…
RAILS: A Robust Adversarial Immune-inspired Learning System
Ren Wang, Tianqi Chen, Stephen Lindsly +3
Adversarial attacks against deep neural networks are continuously evolving. Without effective defenses, they can lead to catastrophic failure. The long-standing and arguably most p…