Search Results for author: Melody Y. Guan

Found 9 papers, 4 papers with code

Making AI Forget You: Data Deletion in Machine Learning

4 code implementations NeurIPS 2019 Antonio Ginart, Melody Y. Guan, Gregory Valiant, James Zou

Intense recent discussions have focused on how to provide individuals with control over when their data can and cannot be used --- the EU's Right To Be Forgotten regulation is an example of this effort.

BIG-bench Machine Learning Clustering

A Surprising Density of Illusionable Natural Speech

no code implementations3 Jun 2019 Melody Y. Guan, Gregory Valiant

Recent work on adversarial examples has demonstrated that most natural inputs can be perturbed to fool even state-of-the-art machine learning systems.

To Trust Or Not To Trust A Classifier

1 code implementation NeurIPS 2018 Heinrich Jiang, Been Kim, Melody Y. Guan, Maya Gupta

Knowing when a classifier's prediction can be trusted is useful in many applications and critical for safely using AI.

Topological Data Analysis

Nonparametric Stochastic Contextual Bandits

no code implementations5 Jan 2018 Melody Y. Guan, Heinrich Jiang

We analyze the $K$-armed bandit problem where the reward for each arm is a noisy realization based on an observed context under mild nonparametric assumptions.

General Classification Image Classification +1

Faster Discovery of Neural Architectures by Searching for Paths in a Large Model

no code implementations ICLR 2018 Hieu Pham, Melody Y. Guan, Barret Zoph, Quoc V. Le, Jeff Dean

We propose Efficient Neural Architecture Search (ENAS), a faster and less expensive approach to automated model design than previous methods.

Neural Architecture Search

Efficient Attention using a Fixed-Size Memory Representation

no code implementations EMNLP 2017 Denny Britz, Melody Y. Guan, Minh-Thang Luong

The standard content-based attention mechanism typically used in sequence-to-sequence models is computationally expensive as it requires the comparison of large encoder and decoder states at each time step.

Translation

Who Said What: Modeling Individual Labelers Improves Classification

1 code implementation26 Mar 2017 Melody Y. Guan, Varun Gulshan, Andrew M. Dai, Geoffrey E. Hinton

We also show that our method performs better than competing algorithms by Welinder and Perona (2010), and by Mnih and Hinton (2012).

Classification General Classification

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