A statistical framework for differential privacy (2008)
Wasserman, Larry, Zhou, Shuheng
One goal of statistical privacy research is to construct a data release mechanism that protects individual privacy while preserving information content. Specifically, a randomized mechanism takes an...
Spectral Connectivity Analysis (2008)
Spectral kernel methods are techniques for transforming data into a coordinate system that efficiently reveals the geometric structure - in particular, the "connectivity" - of the data. These methods...
Revealing components of the galaxy population through nonparametric techniques (2008)
Bamford, Steven P., Rojas, Alex L., Nichol, Robert C., Miller, Christopher J., Wasserman, Larry, Genovese, Christopher R., ...
The distributions of galaxy properties vary with environment, and are often multimodal, suggesting that the galaxy population may be a combination of multiple components. The behaviour of these...
Rejoinder of: Treelets--An adaptive multi-scale basis for spare unordered data (2008)
Lee, Ann B., Nadler, Boaz, Wasserman, Larry
Rejoinder of "Treelets--An adaptive multi-scale basis for spare unordered data" [arXiv:0707.0481]
Inference for the Dark Energy Equation of State Using Type Ia Supernova Data (2008)
Genovese, Christopher R., Freeman, Peter, Wasserman, Larry, Nichol, Robert C., Miller, Christopher
The surprising discovery of an accelerating universe led cosmologists to posit the existence of ``dark energy'' -- a mysterious energy field that permeates the universe. Understanding dark energy has...
On the path density of a gradient field (2008)
Genovese, Christopher R., Perone-Pacifico, Marco, Verdinelli, Isabella, Wasserman, Larry
We consider the problem of reliably finding filaments in point clouds. Realistic data sets often have numerous filaments of various sizes and shapes. Statistical techniques exist for for finding one...
Discussion of: Statistical analysis of an archeological find (2008)
Höfling, Holger, Wasserman, Larry
Discussion of ``Statistical analysis of an archeological find'' by Andrey Feuerverger [arXiv:0804.0079]
Rodeo: Sparse, greedy nonparametric regression (2008)
Lafferty, John, Wasserman, Larry
We present a greedy method for simultaneously performing local bandwidth selection and variable selection in nonparametric regression. The method starts with a local linear estimator with large...
Time Varying Undirected Graphs (2008)
Zhou, Shuheng, Lafferty, John, Wasserman, Larry
Undirected graphs are often used to describe high dimensional distributions. Under sparsity conditions, the graph can be estimated using $\ell_1$ penalization methods. However, current methods assume...
Ravikumar, Pradeep, Lafferty, John, Liu, Han, Wasserman, Larry
We present a new class of methods for high-dimensional nonparametric regression and classification called sparse additive models (SpAM). Our methods combine ideas from sparse linear modeling and...
Treelets--An adaptive multi-scale basis for sparse unordered data (2007)
Lee, Ann B., Nadler, Boaz, Wasserman, Larry
In many modern applications, including analysis of gene expression and text documents, the data are noisy, high-dimensional, and unordered--with no particular meaning to the given order of the...
Zhou, Shuheng, Lafferty, John, Wasserman, Larry
Recent research has studied the role of sparsity in high dimensional regression and signal reconstruction, establishing theoretical limits for recovering sparse models from sparse data. This line of...
Mapping the Cosmological Confidence Ball Surface (2007)
Bryan, Brent, Schneider, Jeff, Miller, Christopher J., Nichol, Robert C., Genovese, Christopher, Wasserman, Larry
We present a new technique to compute simultaneously valid confidence intervals for a set of model parameters. We apply our method to the Wilkinson Microwave Anisotropy Probe's (WMAP) Cosmic...
Multi-Stage Variable Selection: Screen and Clean (2007)
Wasserman, Larry, Roeder, Kathryn
This paper explores the following question: what kind of statistical guarantees can be given when doing variable variable in high dimensional models? In particular, we look at the error rates and...
Adaptive Confidence Bands (2007)
Genovese, Christopher R., Wasserman, Larry
We show that there do not exist adaptive confidence bands for curve estimation except under very restrictive assumptions. We propose instead to construct adaptive bands that cover a surrogate...
Improving power in genome-wide association studies: weights tip the scale (2007)
Roeder, Kathryn, Devlin, Bernie, Wasserman, Larry
Genome-wide association analysis has generated much discussion about how to preserve power to detect signals despite the detrimental effect of multiple testing on power. We develop a weighted...
Correlation-sharing for detection of differential gene expression (2006)
Tibshirani, Robert, Wasserman, Larry
We propose a method for detecting differential gene expression that exploits the correlation between genes. Our proposal averages the univariate scores of each feature with the scores in correlation...
Weighted Hypothesis Testing (2006)
Wasserman, Larry, Roeder, Kathryn
The power of multiple testing procedures can be increased by using weighted p-values (Genovese, Roeder and Wasserman 2005). We derive the optimal weights and we show that the power is remarkably...
Statistical Computations with AstroGrid and the Grid (2005)
Nichol, Robert C, Smith, Garry, Miller, Christopher J, Genovese, Chris, Wasserman, Larry, Bryan, Brent, ...
We outline our first steps towards marrying two new and emerging technologies; the Virtual Observatory (e.g, AstroGrid) and the computational grid. We discuss the construction of VOTechBroker, which...
Massive Science with VO and Grids (2005)
Nichol, Robert, Smith, Garry, Miller, Christopher, Freeman, Peter, Genovese, Chris, Wasserman, Larry, ...
There is a growing need for massive computational resources for the analysis of new astronomical datasets. To tackle this problem, we present here our first steps towards marrying two new and...
Rodeo: Sparse Nonparametric Regression in High Dimensions (2005)
Lafferty, John, Wasserman, Larry
We present a greedy method for simultaneously performing local bandwidth selection and variable selection in nonparametric regression. The method starts with a local linear estimator with large...
Confidence sets for nonparametric wavelet regression (2005)
Genovese, Christopher R., Wasserman, Larry
We construct nonparametric confidence sets for regression functions using wavelets that are uniform over Besov balls. We consider both thresholding and modulation estimators for the wavelet...
Confidence sets for nonparametric wavelet regression (2005)
Genovese, Christopher R., Wasserman, Larry
We construct nonparametric confidence sets for regression functions using wavelets that are uniform over Besov balls. We consider both thresholding and modulation estimators for the wavelet...
Nonparametric Inference for the Cosmic Microwave Background (2004)
Genovese, Christopher R., Miller, Christopher J., Nichol, Robert C., Arjunwadkar, Mihir, Wasserman, Larry
The Cosmic Microwave Background (CMB), which permeates the entire Universe, is the radiation left over from just 380,000 years after the Big Bang. On very large scales, the CMB radiation field is...
A stochastic process approach to false discovery control (2004)
Genovese, Christopher, Wasserman, Larry
This paper extends the theory of false discovery rates (FDR) pioneered by Benjamini and Hochberg [J. Roy. Statist. Soc. Ser. B 57 (1995) 289-300]. We develop a framework in which the False Discovery...
A stochastic process approach to false discovery control (2004)
Genovese, Christopher, Wasserman, Larry
This paper extends the theory of false discovery rates (FDR) pioneered by Benjamini and Hochberg [J. Roy. Statist. Soc. Ser. B 57 (1995) 289–300]. We develop a framework in which the False...
Nonparametric Inference for the Cosmic Microwave Background (2004)
Genovese, Christopher R., Miller, Christopher J., Nichol, Robert C., Arjunwadkar, Mihir, Wasserman, Larry
The cosmic microwave background (CMB), which permeates the entire Universe, is the radiation left over from just 380,000 years after the Big Bang. On very large scales, the CMB radiation field is...
Multi-Tree Methods for Statistics on Very Large Datasets in Astronomy (2004)
Gray, Alexander G., Moore, Andrew W., Nichol, Robert C., Connolly, Andrew J., Genovese, Christopher, Wasserman, Larry
Many fundamental statistical methods have become critical tools for scientific data analysis yet do not scale tractably to modern large datasets. This paper will describe very recent algorithms based...
Prior Distributions for the Bivariate Binomial (2002)
Nick Polson, Polson And, Larry Wasserman
erties since we allow them to depend on the parameter of interest. Some key words: Jeffreys prior; Multivariate binomial; Nuisance parameter; Reference prior. 1. INTRODUCTION Crowder & Sweeting...
Iterative Markov Chain Monte Carlo Computation of Reference Priors and Minimax Risk (2001)
John Lafferty, Larry Wasserman
We present an iterative Markov chain Monte Carlo algorithm for computing reference priors and minimax risk for general parametric families. Our approach uses MCMC techniques based on the...
A Non-parametric Analysis of the CMB Power Spectrum (2001)
Miller, Christopher J., Nichol, Robert C., Genovese, Christopher, Wasserman, Larry
We examine Cosmic Microwave Background (CMB) temperature power spectra from the BOOMERANG, MAXIMA, and DASI experiments. We non-parametrically estimate the true power spectrum with no model...
Non-Parametric Inference in Astrophysics (2001)
Wasserman, Larry, Miller, Christopher J., Nichol, Robert C., Genovese, Chris, Jang, Woncheol, Connolly, Andrew J., ...
We discuss non-parametric density estimation and regression for astrophysics problems. In particular, we show how to compute non-parametric confidence intervals for the location and size of peaks of...
Controlling the False Discovery Rate in Astrophysical Data Analysis (2001)
Miller, Christopher J., Genovese, Christopher, Nichol, Robert C., Wasserman, Larry, Connolly, Andrew, Reichart, Daniel, ...
The False Discovery Rate (FDR) is a new statistical procedure to control the number of mistakes made when performing multiple hypothesis tests, i.e. when comparing many data against a given model...
Rates of convergence of posterior distributions (2001)
Shen, Xiaotong, Wasserman, Larry
We compute the rate at which the posterior distribution concentrates around the true parameter value. The spaces we work in are quite general and include in finite dimensional cases. The rates are...
Fast Algorithms and Efficient Statistics: N-point Correlation Functions (2000)
Moore, Andrew, Connolly, Andy, Genovese, Chris, Gray, Alex, Grone, Larry, Kanidoris II, Nick, ...
We present here a new algorithm for the fast computation of N-point correlation functions in large astronomical data sets. The algorithm is based on kdtrees which are decorated with cached sufficient...
Exponential Language Models, Logistic Regression, and Semantic Coherence (2000)
Can Cai, Ronald Rosenfeld, Larry Wasserman
In this paper, we modify the traditional trigram model by using utterance-level semantic coherence features in an exponential model. The semantic coherence features are collected by measuring the...
Rates of convergence for the Gaussian mixture sieve (2000)
Genovese, Christopher R., Wasserman, Larry
Gaussian mixtures provide a convenient method of density estimation that lies somewhere between parametric models and kernel density estimators.When the number of components of the mixture is allowed...
Ronald Rosenfeld, Larry Wasserman, Can Cai, Xiaojin Zhu
Whole sentence exponential language models directly model the probability of an entire sentence using arbitrary computable properties of that sentence. We present an interactive methodology for...
The nearby M-dwarf system Gliese 866 revisited (1999)
Woitas, Jens, Leinert, Christoph, Jahreiß, Hartmut, Henry, Todd, Franz, Otto, Wasserman, Larry
We present an improved orbit determination for the visual pair in the M-dwarf triple system Gliese 866 that is based on new speckle-interferometric and HST observations. The system mass is M = 0.34...
Sebastian Thrun, Christos Faloutsos, Tom Mitchell, Larry Wasserman
This report summarizes the CONALD meeting, which took place June 11-13, 1998, at Carnegie Mellon University. CONALD brought together an interdisciplinary group of scientists, concerned with decision...
Sebastian Thrun, Christos Faloutsos, Tom Mitchell, Larry Wasserman
This report summarizes the CONALD meeting, which took place June 11-13, 1998, at Carnegie Mellon University. CONALD brought together an interdisciplinary group of scientists, concerned with decision...
Sebastian Thrun, Christos Faloutsos, Tom Mitchell, Larry Wasserman
This report summarizes the CONALD meeting, which took place June 11-13, 1998, at Carnegie Mellon University. CONALD brought together an interdisciplinary group of scientists, concerned with decision...
Sebastian Thrun, Christos Faloutsos, Tom Mitchell, Larry Wasserman
This report summarizes the CONALD meeting, which took place June 11-13, 1998, at Carnegie Mellon University. CONALD brought together an interdisciplinary group of scientists, concerned with decision...
Sebastian Thrun, Christos Faloutsos, Tom Mitchell, Larry Wasserman
This report summarizes the CONALD meeting, which took place June 11-13, 1998, at Carnegie Mellon University. CONALD brought together an interdisciplinary group of scientists, concerned with decision...
Flexible Parametric Measurement Error Models (1999)
Raymond J. Carroll, Kathryn Roeder, Larry Wasserman
Inferences in measurement error models can be sensitive to modeling assumptions. Specifically, if the model is incorrect then the estimates can be inconsistent. To reduce sensitivity to modeling...
Flexible Parametric Measurement Error Models (1999)
Raymond J. Carroll, Kathryn Roeder, Larry Wasserman
Inferences in measurement error models can be sensitive to modeling assumptions. Specifically, if the model is incorrect then the estimates can be inconsistent. To reduce sensitivity to modeling...
The consistency of posterior distributions in nonparametric problems (1999)
Barron, Andrew, Schervish, Mark J., Wasserman, Larry
We give conditions that guarantee that the posterior probability of every Hellinger neighborhood of the true distribution tends to 1 almost surely. The conditions are (1) a requirement that the prior...
Sebastian Thrun, Christos Faloutsos, Tom Mitchell, Larry Wasserman
this report. Finally, we would like to thank all participants who contributed to a lively meeting
Rates Of Convergence For The Gaussian Mixture Sieve (1998)
Chris Genovese, Larry Wasserman
Gaussian mixtures provide a convenient method of density estimation that lies somewhere between parametric models and kernel...
Rates Of Convergence For The Gaussian Mixture Sieve (1998)
Chris Genovese, Larry Wasserman
this paper, we bound the rate of convergence. (Rates of convergence for the mixing distribution function have been studied in Chen (1995).) Let OE(x; ; oe) denote a Gaussian density with mean and...
Sebastian Thrun, Christos Faloutsos, Tom Mitchell, Larry Wasserman
This report summarizes the CONALD meeting, which took place June 11-13, 1998, at Carnegie Mellon University. CONALD brought together an interdisciplinary group of scientists, concerned with decision...
Sebastian Thrun, Christos Faloutsos, Tom Mitchell, Larry Wasserman
This report summarizes the CONALD meeting, which took place June 11-13, 1998, at Carnegie Mellon University. CONALD brought together an interdisciplinary group of scientists, concerned with decision...
Sebastian Thrun, Christos Faloutsos, Tom Mitchell, Larry Wasserman
This report summarizes the CONALD meeting, which took place June 11-13, 1998, at Carnegie Mellon University. CONALD brought together an interdisciplinary group of scientists, concerned with decision...
Sebastian Thrun, Christos Faloutsos, Tom Mitchell, Larry Wasserman
This report summarizes the CONALD meeting, which took place June 11-13, 1998, at Carnegie Mellon University. CONALD brought together an interdisciplinary group of scientists, concerned with decision...
A Note on Profile Likelihood, Least Favourable Families and Kullback-Leibler Distance. (1998)
Tibshirani, Robert, Wasserman, Larry
Several methods exist for reducing higher dimensional problems to a single parameter. These include the profile likelihood, least favourable families and methods based on the Kullback-Leibler...
Sebastian Thrun, Christos Faloutsos, Tom Mitchell, Larry Wasserman
This report summarizes the CONALD meeting, which took place June 11-13, 1998, at Carnegie Mellon University. CONALD brought together an interdisciplinary group of scientists, concerned with decision...
Bayesian goodness-of-fit testing using infinite-dimensional exponential families (1998)
Verdinelli, Isabella, Wasserman, Larry
We develop a nonparametric Bayes factor for testing the fit of a parametric model. We begin with a nominal parametric family which we then embed into an infinite-dimensional exponential family. The...
Statistical Inference For A Computational Model Of Cognition (1998)
Y Bruno, James Mcclell, Larry Wasserman
this paper. Ultimately, we shall be concerned with measuring the evidence in favor of the hypothesis that changing a single parameter in the net suffices to explain the effect of amphetamines. We...
Statistical Inference For A Computational Model Of (1998)
Y Bruno, James Mcclell, Larry Wasserman
this paper. Ultimately, we shall be concerned with measuring the evidence in favor of the hypothesis that changing a single parameter in the net suffices to explain the effect of amphetamines. We...
Asymptotic Properties of Nonparametric Bayesian Procedures (1998)
This chapter provides a brief review of some large sample frequentist properties of nonparametric Bayesian procedures. The review is not comprehensive, but rather, is meant to give a simple,...
Bayesian Model Selection and Model Averaging (1997)
This paper reviews the Bayesian approach to model selection and model averaging. In this review, I emphasize objective Bayesian methods based on noninformative priors. I will also discuss...
The Consistency of Posterior Distributions in Nonparametric Problems (1997)
Andrew Barron, Mark J. Schervish, Larry Wasserman
We give conditions that guarantee that the posterior probability of every Hellinger...
The Consistency Of Posterior Distributions In Nonparametric Problems (1997)
Andrew Barron, Mark J. Schervish, Larry Wasserman
this paper is to provide a relatively simple, self-contained proof of consistency in Hellinger distance (which is equivalent to consistency in total variation) using only a few conditions like those...
Symmetric, coherent, Choquet capacities (1996)
Kadane, Joseph B., Wasserman, Larry
Choquet capacities are a generalization of probability measures that arise in robustness, decision theory and game theory. Many capacities that arise in robustness are symmetric or can be transformed...
Local sensitivity diagnostics for Bayesian inference (1995)
Gustafson, Paul, Wasserman, Larry
We investigate diagnostics for quantifying the effect of small changes to the prior distribution over a k-dimensional parameter space. We show that several previously suggested diagnostics, such as...
Practical Bayesian Density Estimation Using Mixtures Of Normals (1995)
Kathryn Roeder, Larry Wasserman
this paper, we propose some solutions to these problems. Our goal is to come up with a simple, practical method for estimating the density. This is an interesting problem in its own right, as well as...
Practical Bayesian Density Estimation Using Mixtures Of Normals (1995)
Kathryn Roeder, Larry Wasserman
this paper, we propose some solutions to these problems. Our goal is to come up with a simple, practical method for estimating the density. This is an interesting problem in its own right, as well as...
A Reference Bayesian Test for Nested Hypotheses And its Relationship to the Schwarz Criterion (1995)
Robert E. Kass, Larry Wasserman
To compute a Bayes factor for testing H 0 : / = / 0 in the presence of a nuisance parameter fi, priors under the null and alternative hypotheses must be chosen. As in Bayesian estimation, an...
Symmetric, Coherent, Choquet Capacities (1995)
Joseph B. Kadane, Larry Wasserman
This paper is concerned with such characterizations. In particular, we are interested in the following question: what are the extreme points in the set of all distribution functions corresponding to...
Symmetric, Coherent, Choquet Capacities (1995)
Joseph B. Kadane, Larry Wasserman
This paper is concerned with such characterizations. In particular, we are interested in the following question: what are the extreme points in the set of all distribution functions corresponding to...
April 12, 1995 Symmetric, Coherent, Choquet Capacities (1995)
Joseph B. Kadane, Larry Wasserman
This paper is concerned with such characterizations. In particular, we are interested in the following question: what are the extreme points in the set of all distribution functions corresponding to...
Divisive Conditioning: Further Results on Dilation (1995)
Timothy Herron, Teddy Seidenfeld, Larry Wasserman
this paper, we further investigate dilation in several models. In particular, we consider conditions under which dilation persists under marginalization and we quantify the degree of dilation. We...
Formal Rules for Selecting Prior Distributions: A Review and Annotated Bibliography (1995)
Robert E. Kass, Larry Wasserman
Subjectivism has become the dominant philosophical foundation for Bayesian inference. Yet, in practice, most Bayesian analyses are performed with so-called "noninformative " priors, that is, priors...
Using Linkage Genome Scans to Improve Power of Association in Genome Scans
Roeder, Kathryn, Bacanu, Silvi-Alin, Wasserman, Larry, Devlin, B.
Scanning the genome for association between markers and complex diseases typically requires testing hundreds of thousands of genetic polymorphisms. Testing such a large number of hypotheses...
Tzeng, Jung-Ying, Devlin, B., Wasserman, Larry, Roeder, Kathryn
The observation that haplotypes from a particular region of the genome differ between affected and unaffected individuals or between chromosomes transmitted to affected individuals versus those not...
Using Linkage Genome Scans to Improve Power of Association in Genome Scans
Roeder, Kathryn, Bacanu, Silvi-Alin, Wasserman, Larry, Devlin, B.
Scanning the genome for association between markers and complex diseases typically requires testing hundreds of thousands of genetic polymorphisms. Testing such a large number of hypotheses...