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We study the structure and learnability of sums of independent integer random variables (SIIRVs).
A measure of asymptotic efficiency for tests of a hypothesis based on the sum of observations
H. Chernoff · 1952
Earlier work this paper cites.
ε \varepsilon -entropy and ε \varepsilon -capacity of sets in function spaces
A. N. Kolmogorov and V. M. Tihomirov · 1959
Earlier work this paper cites.
Probability inequalities for sums of bounded random variables
W. Hoeffding · 1963
Earlier work this paper cites.
Metric entropy and approximation
G. G. Lorentz · 1966
Earlier work this paper cites.
Statistical Inference under Order Restrictions
R.E. Barlow, D.J. Bartholomew, J.M. Bremner, and H.D. Brunk · 1972
Earlier work this paper cites.
Metric entropy of some classes of sets with differentiable boundaries
R.M Dudley · 1974
Earlier work this paper cites.
Principles of mathematical analysis
W. Rudin · 1976
Earlier work this paper cites.
Deux remarques sur l’estimation
P. Assouad · 1983
Earlier work this paper cites.
Approximation of binomial distributions by infinitely divisible ones
E. L. Presman · 1983
Earlier work this paper cites.
Nonparametric Density Estimation: The L 1 L_{1} View
L. Devroye and L. Györfi · 1985
Earlier work this paper cites.
Rates of convergence of minimum distance estimators and Kolmogorov’s entropy
Y. G. Yatracos · 1985
Earlier work this paper cites.
On estimating a density using Hellinger distance and some other strange facts
L. Birgé · 1986
Earlier work this paper cites.
Precision of approximation of the generalized binomial distribution by convolutions of poisson measures
J. Kruopis · 1986
Earlier work this paper cites.
On the kolmogorov complexity of functions of finite smoothness
Y. Makovoz · 1986
Earlier work this paper cites.
Density Estimation
B. W. Silverman · 1986
Earlier work this paper cites.
Learnability and the Vapnik-Chervonenkis dimension
A. Blumer, A. Ehrenfeucht, D. Haussler, and M. Warmuth · 1989
Earlier work this paper cites.
Entropy, compactness and the approximation of operators
B. Carl and I. Stephani · 1990
Earlier work this paper cites.
On density estimation in the view of kolmogorov’s ideas in approximation theory
R. Hasminskii and I. Ibragimov · 1990
Earlier work this paper cites.
Recent developments in nonparametric density estimation
A. J. Izenman · 1991
Earlier work this paper cites.
Poisson Approximation
A.D. Barbour, L. Holst, and S. Janson · 1992
Earlier work this paper cites.
Multivariate Density Estimation: Theory, Practice and Visualization
D.W. Scott · 1992
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On the learnability of discrete distributions
M. Kearns, Y. Mansour, D. Ron, R. Rubinfeld, R. Schapire, and L. Sellie · 1994
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An Introduction to Computational Learning Theory
M. Kearns and U. Vazirani · 1994
Cited alongside, same era.
Function spaces, entropy numbers, differential operators
D. E. Edmunds and H. Triebel · 1996
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Weak convergence and empirical processes
A. W. van der Vaart and J. A. Wellner · 1996
Cited alongside, same era.
Statistical applications of the Poisson-Binomial and Conditional Bernoulli Distributions
S.X. Chen and J.S. Liu · 1997
Cited alongside, same era.
Polynomial learning of distribution families
M. Belkin and K. Sinha · 2010
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From zero-bias to discretized normal approximation
L. H. Y. Chen and Y. K. Leong · 2010
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Efficiently learning mixtures of two Gaussians
A. T. Kalai, A. Moitra, and G. Valiant · 2010
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Settling the polynomial learnability of mixtures of Gaussians
A. Moitra and G. Valiant · 2010
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Normal Approximation by Stein’s Method
L. Chen, L. Goldstein, and Q.-M. Shao · 2011
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Geometric Approximation Algorithms
S. Har-peled · 2011
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Learning k k -modal distributions via testing
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Mutual information, metric entropy and cumulative relative entropy risk
D. Haussler and M. Opper · 1997
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Estimating a mixture of two product distributions
Y. Freund and Y. Mansour · 1999
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Information-theoretic determination of minimax rates of convergence
Y. Yang and A. Barron · 1999
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Binomial approximation to the Poisson binomial distribution: The Krawtchouk expansion
B. Roos · 2000
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Learning mixtures of arbitrary Gaussians
S. Arora and R. Kannan · 2001
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Combinatorial methods in density estimation
L. Devroye and G. Lugosi · 2001
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C. Daskalakis, I. Diakonikolas, and R.A. Servedio · 2012
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Learning Poisson Binomial Distributions
C. Daskalakis, I. Diakonikolas, and R.A. Servedio · 2012
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Learning Sums of Independent Integer Random Variables
C. Daskalakis, I. Diakonikolas, R. O’Donnell, R.A. Servedio, and L. Tan · 2013
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Covering numbers for convex functions
A. Guntuboyina and B. Sen · 2013
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Efficient density estimation via piecewise polynomial approximation
S. Chan, I. Diakonikolas, R. Servedio, and X. Sun · 2014
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Near-optimal density estimation in near-linear time using variable-width histograms
S. Chan, I. Diakonikolas, R. Servedio, and X. Sun · 2014
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Sparse covers for sums of indicators
C. Daskalakis and C. Papadimitriou · 2014
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Nonparametric Estimation under Shape Constraints: Estimators, Algorithms and Asymptotics
P. Groeneboom and G. Jongbloed · 2014
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Sample-optimal density estimation in nearly-linear time
J. Acharya, I. Diakonikolas, J. Li, and L. Schmidt · 2015
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On the complexity of nash equilibria in anonymous games
X. Chen, D. Durfee, and A. Orfanou · 2015
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Learning poisson binomial distributions
C. Daskalakis, I. Diakonikolas, and R. A. Servedio · 2015
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The fourier transform of poisson multinomial distributions and its algorithmic applications
I. Diakonikolas, D. M. Kane, and A. Stewart · 2015
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Properly learning poisson binomial distributions in almost polynomial time
I. Diakonikolas, D. M. Kane, and A. Stewart · 2015
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On the structure, covering, and learning of poisson multinomial distributions
C. Daskalakis, G. Kamath, and C. Tzamos · 2015
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