activity
19932022
most citedGradientless Descent: High-Dimensional Zeroth-Order Optimization

39 citations · 92 across the 10 of their papers we have counts for

collaborators

10 papers

cs.LG2022★ 4 cited

Open Source Vizier: Distributed Infrastructure and API for Reliable and Flexible Blackbox Optimization

Xingyou Song, Sagi Perel, Chansoo Lee +2

Vizier is the de-facto blackbox and hyperparameter optimization service across Google, having optimized some of Google's largest products and research efforts. To operate at the sc…

cs.LG2022★ 19 cited

Towards Learning Universal Hyperparameter Optimizers with Transformers

Yutian Chen, Xingyou Song, Chansoo Lee +9

Meta-learning hyperparameter optimization (HPO) algorithms from prior experiments is a promising approach to improve optimization efficiency over objective functions from a similar…

cs.LG2019★ 39 cited

Gradientless Descent: High-Dimensional Zeroth-Order Optimization

Daniel Golovin, John Karro, Greg Kochanski +3

Zeroth-order optimization is the process of minimizing an objective , given oracle access to evaluations at adaptively chosen inputs . In this paper, we present two simple…

stat.ME2015

Categorical Judgment with a Variable Decision Rule

Burton Rosner, Greg Kochanski

A new Thurstonian rating scale model uses a variable decision rule (VDR) that incorporates three previously formulated, distinct decision rules. The model includes probabilities fo…

cs.SD2012

Using Mimicry to Learn about Mental Representations

Greg Kochanski

Phonology typically describes speech in terms of discrete signs like features. The field of intonational phonology uses discrete accents to describe intonation and prosody. But, ar…

cs.SD2011★ 1 cited

Detecting gross alignment errors in the Spoken British National Corpus

Ladan Baghai-Ravary, Sergio Grau, Greg Kochanski

The paper presents methods for evaluating the accuracy of alignments between transcriptions and audio recordings. The methods have been applied to the Spoken British National Corpu…

cs.SD2010★ 1 cited

Should Corpora be Big, Rich, or Dense?

Greg P. Kochanski, Chilin Shih, Ryan Shosted

In this paper, we ask what properties makes a large corpus more or less useful. We suggest that size, by itself, should not be the ultimate goal of building a corpus. Large-scale c…

math.NA2010★ 3 cited

Bootstrap Markov chain Monte Carlo and optimal solutions for the Law of Categorical Judgment (Corrected)

Greg Kochanski, Burton S. Rosner

A novel procedure is described for accelerating the convergence of Markov chain Monte Carlo computations. The algorithm uses an adaptive bootstrap technique to generate candidate s…

astro-ph1996★ 10 cited

Flickering Faint Galaxies: Few and Far Between

Greg P. Kochanski, J. Anthony Tyson, Philippe Fischer

Optical variability in galaxies at high redshift is a tracer of evolution in AGN activity, and should provide a useful constraint on models of galaxy evolution, AGN structure, and…

astro-ph1993★ 15 cited

Optimal Addition of Images for Detection and Photometry

Philippe Fischer, Greg P. Kochanski

In this paper we describe weighting techniques used for the optimal coaddition of CCD frames with differing characteristics. Optimal means maximum signal-to-noise (s/n) for stellar…