Search Results for author: Kristy Choi

Found 8 papers, 4 papers with code

Featurized Density Ratio Estimation

1 code implementation5 Jul 2021 Kristy Choi, Madeline Liao, Stefano Ermon

Density ratio estimation serves as an important technique in the unsupervised machine learning toolbox.

Data Augmentation Density Ratio Estimation +1

Robust Representation Learning via Perceptual Similarity Metrics

no code implementations11 Jun 2021 Saeid Asgari Taghanaki, Kristy Choi, Amir Khasahmadi, Anirudh Goyal

A fundamental challenge in artificial intelligence is learning useful representations of data that yield good performance on a downstream task, without overfitting to spurious input features.

Representation Learning

Neural Network Compression for Noisy Storage Devices

no code implementations15 Feb 2021 Berivan Isik, Kristy Choi, Xin Zheng, Tsachy Weissman, Stefano Ermon, H. -S. Philip Wong, Armin Alaghi

We propose a radically different approach that: (i) employs analog memories to maximize the capacity of each memory cell, and (ii) jointly optimizes model compression and physical storage to maximize memory utility.

Neural Network Compression

Learning Task-Relevant Features via Contrastive Input Morphing

no code implementations1 Jan 2021 Saeid Asgari, Kristy Choi, Amir Hosein Khasahmadi, Anirudh Goyal

A fundamental challenge in artificial intelligence is learning useful representations of data that yield good performance on a downstream classification task, without overfitting to spurious input features.

Representation Learning

Encoding Musical Style with Transformer Autoencoders

no code implementations ICML 2020 Kristy Choi, Curtis Hawthorne, Ian Simon, Monica Dinculescu, Jesse Engel

We consider the problem of learning high-level controls over the global structure of generated sequences, particularly in the context of symbolic music generation with complex language models.

Music Generation

Fair Generative Modeling via Weak Supervision

1 code implementation ICML 2020 Kristy Choi, Aditya Grover, Trisha Singh, Rui Shu, Stefano Ermon

Real-world datasets are often biased with respect to key demographic factors such as race and gender.

Image Generation

Meta-Amortized Variational Inference and Learning

1 code implementation5 Feb 2019 Mike Wu, Kristy Choi, Noah Goodman, Stefano Ermon

Despite the recent success in probabilistic modeling and their applications, generative models trained using traditional inference techniques struggle to adapt to new distributions, even when the target distribution may be closely related to the ones seen during training.

Density Estimation Image Classification +1

Neural Joint Source-Channel Coding

1 code implementation19 Nov 2018 Kristy Choi, Kedar Tatwawadi, Aditya Grover, Tsachy Weissman, Stefano Ermon

For reliable transmission across a noisy communication channel, classical results from information theory show that it is asymptotically optimal to separate out the source and channel coding processes.

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