b'Yutian Chen'

research

∙ 05/13/2023

GPT-Sentinel: Distinguishing Human and ChatGPT Generated Content

This paper presents a novel approach for detecting ChatGPT-generated vs....

0 Yutian Chen, et al. ∙

research

∙ 10/10/2022

Multi-step Planning for Automated Hyperparameter Optimization with OptFormer

As machine learning permeates more industries and models become more exp...

10 Lucio M. Dery, et al. ∙

research

∙ 05/26/2022

Towards Learning Universal Hyperparameter Optimizers with Transformers

Meta-learning hyperparameter optimization (HPO) algorithms from prior ex...

9 Yutian Chen, et al. ∙

research

∙ 05/12/2022

A Generalist Agent

Inspired by progress in large-scale language modeling, we apply a simila...

12 Scott Reed, et al. ∙

research

∙ 02/05/2022

Importance Weighting Approach in Kernel Bayes' Rule

We study a nonparametric approach to Bayesian computation via feature me...

0 Liyuan Xu, et al. ∙

research

∙ 10/20/2021

Shaking the foundations: delusions in sequence models for interaction and control

The recent phenomenal success of language models has reinvigorated machi...

68 Pedro A. Ortega, et al. ∙

research

∙ 06/18/2021

Active Offline Policy Selection

This paper addresses the problem of policy selection in domains with abu...

12 Ksenia Konyushkova, et al. ∙

research

∙ 05/21/2021

On Instrumental Variable Regression for Deep Offline Policy Evaluation

We show that the popular reinforcement learning (RL) strategy of estimat...

26 Yutian Chen, et al. ∙

research

∙ 03/30/2021

Benchmarks for Deep Off-Policy Evaluation

Off-policy evaluation (OPE) holds the promise of being able to leverage ...

13 Justin Fu, et al. ∙

research

∙ 03/17/2021

Regularized Behavior Value Estimation

Offline reinforcement learning restricts the learning process to rely on...

8 Caglar Gulcehre, et al. ∙

research

∙ 12/29/2020

Myocardial Segmentation of Cardiac MRI Sequences with Temporal Consistency for Coronary Artery Disease Diagnosis

Coronary artery disease (CAD) is the most common cause of death globally...

1 Yutian Chen, et al. ∙

research

∙ 11/24/2020

Synth2Aug: Cross-domain speaker recognition with TTS synthesized speech

In recent years, Text-To-Speech (TTS) has been used as a data augmentati...

0 Yiling Huang, et al. ∙

research

∙ 11/14/2020

Towards transformation-resilient provenance detection of digital media

Advancements in deep generative models have made it possible to synthesi...

7 Jamie Hayes, et al. ∙

research

∙ 11/06/2020

Large-scale multilingual audio visual dubbing

We describe a system for large-scale audiovisual translation and dubbing...

3 Yi Yang, et al. ∙

research

∙ 10/14/2020

Learning Deep Features in Instrumental Variable Regression

Instrumental variable (IV) regression is a standard strategy for learnin...

21 Liyuan Xu, et al. ∙

research

∙ 10/06/2020

Sequential Changepoint Detection in Neural Networks with Checkpoints

We introduce a framework for online changepoint detection and simultaneo...

0 Michalis K. Titsias, et al. ∙

research

∙ 09/12/2019

Modular Meta-Learning with Shrinkage

Most gradient-based approaches to meta-learning do not explicitly accoun...

6 Yutian Chen, et al. ∙

research

∙ 12/17/2018

Bayesian Optimization in AlphaGo

During the development of AlphaGo, its many hyper-parameters were tuned ...

129 Yutian Chen, et al. ∙

research

∙ 09/27/2018

Sample Efficient Adaptive Text-to-Speech

We present a meta-learning approach for adaptive text-to-speech (TTS) wi...

2 Yutian Chen, et al. ∙

research

∙ 10/27/2017

Few-shot Autoregressive Density Estimation: Towards Learning to Learn Distributions

Deep autoregressive models have shown state-of-the-art performance in de...

0 Scott Reed, et al. ∙

research

∙ 11/11/2016

Learning to Learn without Gradient Descent by Gradient Descent

We learn recurrent neural network optimizers trained on simple synthetic...

0 Yutian Chen, et al. ∙

research

∙ 02/09/2016

Herding as a Learning System with Edge-of-Chaos Dynamics

Herding defines a deterministic dynamical system at the edge of chaos. I...

0 Yutian Chen, et al. ∙

research

∙ 06/30/2015

Scalable Discrete Sampling as a Multi-Armed Bandit Problem

Drawing a sample from a discrete distribution is one of the building com...

0 Yutian Chen, et al. ∙

research

∙ 03/07/2015

Latent Gaussian Processes for Distribution Estimation of Multivariate Categorical Data

Multivariate categorical data occur in many applications of machine lear...

0 Yarin Gal, et al. ∙

research

∙ 11/06/2014

Sublinear-Time Approximate MCMC Transitions for Probabilistic Programs

Probabilistic programming languages can simplify the development of mach...

0 Yutian Chen, et al. ∙

research

∙ 08/09/2014

Bayesian Structure Learning for Markov Random Fields with a Spike and Slab Prior

In recent years a number of methods have been developed for automaticall...

0 Yutian Chen, et al. ∙

research

∙ 04/19/2013

Austerity in MCMC Land: Cutting the Metropolis-Hastings Budget

Can we make Bayesian posterior MCMC sampling more efficient when faced w...

0 Anoop Korattikara, et al. ∙

research

∙ 01/17/2013

Herded Gibbs Sampling

The Gibbs sampler is one of the most popular algorithms for inference in...

0 Luke Bornn, et al. ∙

research

∙ 03/15/2012

Super-Samples from Kernel Herding

We extend the herding algorithm to continuous spaces by using the kernel...

0 Yutian Chen, et al. ∙

Yutian Chen

Featured Co-authors