Alon Orlitsky

Publication Activity (10 Years)

Years Active: 1984-2023
Publications (10 Years): 45

Top Venues

CoRR

ISIT

ICML

NeurIPS

Publications

Ayush Jain, Rajat Sen, Weihao Kong, Abhimanyu Das, Alon Orlitsky
Linear Regression using Heterogeneous Data Batches. CoRR (2023)
Yi Hao, Ayush Jain, Alon Orlitsky, Vaishakh Ravindrakumar
TURF: A Two-factor, Universal, Robust, Fast Distribution Learning Algorithm. CoRR (2022)
Ayush Jain, Alon Orlitsky, Vaishakh Ravindrakumar
Robust estimation algorithms don't need to know the corruption level. CoRR (2022)
Yi Hao, Ayush Jain, Alon Orlitsky, Vaishakh Ravindrakumar
TURF: Two-Factor, Universal, Robust, Fast Distribution Learning Algorithm. ICML (2022)
Yi Hao, Alon Orlitsky
Compressed Maximum Likelihood. ICML (2021)
Ayush Jain, Alon Orlitsky
Robust Density Estimation from Batches: The Best Things in Life are (Nearly) Free. ICML (2021)
Yi Hao, Alon Orlitsky
Data Amplification: Instance-Optimal Property Estimation. ICML (2020)
Yi Hao, Alon Orlitsky
Profile Entropy: A Fundamental Measure for the Learnability and Compressibility of Distributions. NeurIPS (2020)
Ayush Jain, Alon Orlitsky
Linear-Sample Learning of Low-Rank Distributions. NeurIPS (2020)
Ayush Jain, Alon Orlitsky
A General Method for Robust Learning from Batches. NeurIPS (2020)
Yi Hao, Alon Orlitsky
Profile Entropy: A Fundamental Measure for the Learnability and Compressibility of Discrete Distributions. CoRR (2020)
Yi Hao, Ayush Jain, Alon Orlitsky, Vaishakh Ravindrakumar
SURF: A Simple, Universal, Robust, Fast Distribution Learning Algorithm. NeurIPS (2020)
Moein Falahatgar, Mesrob I. Ohannessian, Alon Orlitsky, Venkatadheeraj Pichapati
Towards Competitive N-gram Smoothing. AISTATS (2020)
Ayush Jain, Alon Orlitsky
A General Method for Robust Learning from Batches. CoRR (2020)
Yi Hao, Ayush Jain, Alon Orlitsky, Vaishakh Ravindrakumar
SURF: A Simple, Universal, Robust, Fast Distribution Learning Algorithm. CoRR (2020)
Ayush Jain, Alon Orlitsky
Optimal Robust Learning of Discrete Distributions from Batches. ICML (2020)
Moein Falahatgar, Alon Orlitsky, Venkatadheeraj Pichapati
Optimal Sequential Maximization: One Interview is Enough! ICML (2020)
Ayush Jain, Alon Orlitsky
Linear-Sample Learning of Low-Rank Distributions. CoRR (2020)
Sudeep Kamath, Alon Orlitsky, Venkatadheeraj Pichapati, Ehsan Zobeidi
On Learning Parametric Non-Smooth Continuous Distributions. ISIT (2020)
Yi Hao, Alon Orlitsky
The Broad Optimality of Profile Maximum Likelihood. CoRR (2019)
Yi Hao, Alon Orlitsky
Unified Sample-Optimal Property Estimation in Near-Linear Time. CoRR (2019)
Yi Hao, Alon Orlitsky
The Broad Optimality of Profile Maximum Likelihood. NeurIPS (2019)
Yi Hao, Alon Orlitsky
Data Amplification: Instance-Optimal Property Estimation. CoRR (2019)
Yi Hao, Alon Orlitsky
Unified Sample-Optimal Property Estimation in Near-Linear Time. NeurIPS (2019)
Ayush Jain, Alon Orlitsky
Robust Learning of Discrete Distributions from Batches. CoRR (2019)
Yi Hao, Alon Orlitsky
Doubly-Competitive Distribution Estimation. ICML (2019)
Yi Hao, Alon Orlitsky, Ananda Theertha Suresh, Yihong Wu
Data Amplification: A Unified and Competitive Approach to Property Estimation. CoRR (2019)
Jayadev Acharya, Moein Falahatgar, Ashkan Jafarpour, Alon Orlitsky, Ananda Theertha Suresh
Maximum Selection and Sorting with Adversarial Comparators. J. Mach. Learn. Res. 19 (2018)
Yi Hao, Alon Orlitsky, Venkatadheeraj Pichapati
On Learning Markov Chains. CoRR (2018)
Yi Hao, Alon Orlitsky
Adaptive Estimation of Generalized Distance to Uniformity. ISIT (2018)
Moein Falahatgar, Ayush Jain, Alon Orlitsky, Venkatadheeraj Pichapati, Vaishakh Ravindrakumar
The Limits of Maxing, Ranking, and Preference Learning. ICML (2018)
Yi Hao, Alon Orlitsky, Ananda Theertha Suresh, Yihong Wu
Data Amplification: A Unified and Competitive Approach to Property Estimation. NeurIPS (2018)
Yi Hao, Alon Orlitsky, Venkatadheeraj Pichapati
On Learning Markov Chains. NeurIPS (2018)
Jayadev Acharya, Hirakendu Das, Alon Orlitsky, Ananda Theertha Suresh
A Unified Maximum Likelihood Approach for Estimating Symmetric Properties of Discrete Distributions. ICML (2017)
Moein Falahatgar, Alon Orlitsky, Venkatadheeraj Pichapati, Ananda Theertha Suresh
Maximum Selection and Ranking under Noisy Comparisons. CoRR (2017)
Moein Falahatgar, Mesrob I. Ohannessian, Alon Orlitsky, Venkatadheeraj Pichapati
The power of absolute discounting: all-dimensional distribution estimation. NIPS (2017)
Jayadev Acharya, Alon Orlitsky, Ananda Theertha Suresh, Himanshu Tyagi
Estimating Renyi Entropy of Discrete Distributions. IEEE Trans. Inf. Theory 63 (1) (2017)
Moein Falahatgar, Yi Hao, Alon Orlitsky, Venkatadheeraj Pichapati, Vaishakh Ravindrakumar
Maxing and Ranking with Few Assumptions. NIPS (2017)
Moein Falahatgar, Alon Orlitsky, Venkatadheeraj Pichapati, Ananda Theertha Suresh
Maximum Selection and Ranking under Noisy Comparisons. ICML (2017)
Jayadev Acharya, Hirakendu Das, Alon Orlitsky, Ananda Theertha Suresh
A Unified Maximum Likelihood Approach for Optimal Distribution Property Estimation. CoRR (2016)
Moein Falahatgar, Mesrob I. Ohannessian, Alon Orlitsky
Near-Optimal Smoothing of Structured Conditional Probability Matrices. NIPS (2016)
Jayadev Acharya, Hirakendu Das, Alon Orlitsky, Ananda Theertha Suresh
A Unified Maximum Likelihood Approach for Optimal Distribution Property Estimation. Electron. Colloquium Comput. Complex. 23 (2016)
Moein Falahatgar, Alon Orlitsky, Venkatadheeraj Pichapati, Ananda Theertha Suresh
Learning Markov distributions: Does estimation trump compression? ISIT (2016)
Jayadev Acharya, Moein Falahatgar, Ashkan Jafarpour, Alon Orlitsky, Ananda Theertha Suresh
Maximum Selection and Sorting with Adversarial Comparators and an Application to Density Estimation. CoRR (2016)
Moein Falahatgar, Ashkan Jafarpour, Alon Orlitsky, Venkatadheeraj Pichapati, Ananda Theertha Suresh
Estimating the number of defectives with group testing. ISIT (2016)
Alon Orlitsky, Ananda Theertha Suresh
Competitive Distribution Estimation. CoRR (2015)
Sudeep Kamath, Alon Orlitsky, Dheeraj Pichapati, Ananda Theertha Suresh
On Learning Distributions from their Samples. COLT (2015)
Moein Falahatgar, Ashkan Jafarpour, Alon Orlitsky, Venkatadheeraj Pichapati, Ananda Theertha Suresh
Universal compression of power-law distributions. ISIT (2015)
Moein Falahatgar, Ashkan Jafarpour, Alon Orlitsky, Venkatadheeraj Pichapati, Ananda Theertha Suresh
Universal Compression of Power-Law Distributions. CoRR (2015)
Jayadev Acharya, Alon Orlitsky, Ananda Theertha Suresh, Himanshu Tyagi
The Complexity of Estimating Rényi Entropy. SODA (2015)
Alon Orlitsky, Ananda Theertha Suresh
Competitive Distribution Estimation: Why is Good-Turing Good. NIPS (2015)
Moein Falahatgar, Ashkan Jafarpour, Alon Orlitsky, Venkatadheeraj Pichapati, Ananda Theertha Suresh
Faster Algorithms for Testing under Conditional Sampling. COLT (2015)
Moein Falahatgar, Ashkan Jafarpour, Alon Orlitsky, Venkatadheeraj Pichapathi, Ananda Theertha Suresh
Faster Algorithms for Testing under Conditional Sampling. CoRR (2015)
Jayadev Acharya, Hirakendu Das, Olgica Milenkovic, Alon Orlitsky, Shengjun Pan
String Reconstruction from Substring Compositions. SIAM J. Discret. Math. 29 (3) (2015)
Jayadev Acharya, Ashkan Jafarpour, Alon Orlitsky, Ananda Theertha Suresh
Near-optimal-sample estimators for spherical Gaussian mixtures. CoRR (2014)
Jayadev Acharya, Ashkan Jafarpour, Alon Orlitsky, Ananda Theertha Suresh
Efficient compression of monotone and m-modal distributions. ISIT (2014)
Jayadev Acharya, Ashkan Jafarpour, Alon Orlitsky, Ananda Theertha Suresh
Sublinear algorithms for outlier detection and generalized closeness testing. ISIT (2014)
Alon Orlitsky, Narayana P. Santhanam
Universal compression of Gaussian sources with unknown parameters. CoRR (2014)
Jayadev Acharya, Ashkan Jafarpour, Alon Orlitsky, Ananda Theertha Suresh
Universal Compression of Envelope Classes: Tight Characterization via Poisson Sampling. CoRR (2014)
Ananda Theertha Suresh, Alon Orlitsky, Jayadev Acharya, Ashkan Jafarpour
Near-Optimal-Sample Estimators for Spherical Gaussian Mixtures. NIPS (2014)
Jayadev Acharya, Ashkan Jafarpour, Alon Orlitsky, Ananda Theertha Suresh
Poissonization and universal compression of envelope classes. ISIT (2014)
Jayadev Acharya, Hirakendu Das, Olgica Milenkovic, Alon Orlitsky, Shengjun Pan
String Reconstruction from Substring Compositions. CoRR (2014)
Jayadev Acharya, Alon Orlitsky, Ananda Theertha Suresh, Himanshu Tyagi
The Complexity of Estimating Rényi Entropy. CoRR (2014)
Jayadev Acharya, Hirakendu Das, Olgica Milenkovic, Alon Orlitsky, Shengjun Pan
Quadratic-backtracking algorithm for string reconstruction from substring compositions. ISIT (2014)
Jayadev Acharya, Ashkan Jafarpour, Alon Orlitsky, Ananda Theertha Suresh
Sorting with adversarial comparators and application to density estimation. ISIT (2014)
Jayadev Acharya, Ashkan Jafarpour, Alon Orlitsky, Ananda Theertha Suresh
A Competitive Test for Uniformity of Monotone Distributions. AISTATS (2013)
Panganamala Ramana Kumar, Eyal Kushilevitz, D. Manjunath, Muriel Médard, Alon Orlitsky, R. Srikant
Guest Editorial: In-Network Computation: Exploring the Fundamental Limits. IEEE J. Sel. Areas Commun. 31 (4) (2013)
Jayadev Acharya, Ashkan Jafarpour, Alon Orlitsky, Ananda Theertha Suresh
Optimal Probability Estimation with Applications to Prediction and Classification. COLT (2013)
Jayadev Acharya, Hirakendu Das, Ashkan Jafarpour, Alon Orlitsky, Ananda Theertha Suresh
Tight bounds for universal compression of large alphabets. ISIT (2013)
Hirakendu Das, Ashkan Jafarpour, Alon Orlitsky, Shengjun Pan, Ananda Theertha Suresh
On the query computation and verification of functions. ISIT (2012)
Jayadev Acharya, Hirakendu Das, Alon Orlitsky
Tight Bounds on Profile Redundancy and Distinguishability. NIPS (2012)
Alon Orlitsky, Narayana P. Santhanam, Krishnamurthy Viswanathan, Junan Zhang
On Modeling Profiles instead of Values CoRR (2012)
Jayadev Acharya, Hirakendu Das, Ashkan Jafarpour, Alon Orlitsky, Shengjun Pan, Ananda Theertha Suresh
Competitive Classification and Closeness Testing. COLT (2012)
Jayadev Acharya, Hirakendu Das, Ashkan Jafarpour, Alon Orlitsky, Shengjun Pan
Estimating multiple concurrent processes. ISIT (2012)
Jayadev Acharya, Hirakendu Das, Ashkan Jafarpour, Alon Orlitsky, Shengjun Pan
Competitive Closeness Testing. COLT (2011)
Jayadev Acharya, Hirakendu Das, Alon Orlitsky, Shengjun Pan
Algebraic computation of pattern maximum likelihood. ISIT (2011)
Jayadev Acharya, Ashkan Jafarpour, Alon Orlitsky
Expected query complexity of symmetric boolean functions. Allerton (2011)
Jayadev Acharya, Hirakendu Das, Hosein Mohimani, Alon Orlitsky, Shengjun Pan
Exact calculation of pattern probabilities. ISIT (2010)
Jayadev Acharya, Hirakendu Das, Olgica Milenkovic, Alon Orlitsky, Shengjun Pan
On reconstructing a string from its substring compositions. ISIT (2010)
Anand K. Dhulipala, Christina Fragouli, Alon Orlitsky
Silence-based communication. IEEE Trans. Inf. Theory 56 (1) (2010)
Jayadev Acharya, Hirakendu Das, Alon Orlitsky, Shengjun Pan, Narayana P. Santhanam
Classification using pattern probability estimators. ISIT (2010)
Alon Orlitsky, Shengjun Pan
The maximum likelihood probability of skewed patterns. ISIT (2009)
Jayadev Acharya, Alon Orlitsky, Shengjun Pan
Recent results on pattern maximum likelihood. ITW (2009)
Shengjun Pan, Jayadev Acharya, Alon Orlitsky
The maximum likelihood probability of unique-singleton, ternary, and length-7 patterns. ISIT (2009)
Hirakendu Das, Alon Orlitsky, Narayana P. Santhanam, Junan Zhang
Further results on relative redundancy. ISIT (2008)
Alon Orlitsky, Narayana P. Santhanam, K. Viswanathan
Population estimation with performance guarantees. ISIT (2007)
Anand K. Dhulipala, Christina Fragouli, Alon Orlitsky
Single versus multiple rounds for distributed function computation. ISIT (2007)
Alon Orlitsky, Narayana P. Santhanam, Krishnamurthy Viswanathan, Junan Zhang
Theoretical and Experimental Results on Modeling Low Probabilities. ITW (2006)
Anand K. Dhulipala, Alon Orlitsky
Universal Compression of Markov and Related Sources Over Arbitrary Alphabets. IEEE Trans. Inf. Theory 52 (9) (2006)
Anand K. Dhulipala, Christina Fragouli, Alon Orlitsky
Silence Based Communication for Sensor Networks. ISIT (2006)
Alon Orlitsky, Narayana Santhanam, Junan Zhang
Relative redundancy for large alphabets. ISIT (2006)
Alon Orlitsky, Narayana P. Santhanam, Krishnamurthy Viswanathan, Junan Zhang
Limit Results on Pattern Entropy. IEEE Trans. Inf. Theory 52 (7) (2006)
Alon Orlitsky, Narayana P. Santhanam, K. Viswanathan, Junan Zhang
Convergence of profile based estimators. ISIT (2005)
Sajama, Alon Orlitsky
Estimating and computing density based distance metrics. ICML (2005)
Nikola Jevtic, Alon Orlitsky, Narayana P. Santhanam
A lower bound on compression of unknown alphabets. Theor. Comput. Sci. 332 (1-3) (2005)
Alon Orlitsky, Krishnamurthy Viswanathan, Junan Zhang
Stopping set distribution of LDPC code ensembles. IEEE Trans. Inf. Theory 51 (3) (2005)
Alon Orlitsky, Narayana P. Santhanam, K. Viswanathan, Narayana Zhang
Innovation and pattern entropy of stationary processes. ISIT (2005)
Sajama, Alon Orlitsky
Supervised dimensionality reduction using mixture models. ICML (2005)
Alon Orlitsky, Narayana P. Santhanam, Junan Zhang
Universal compression of memoryless sources over unknown alphabets. IEEE Trans. Inf. Theory 50 (7) (2004)
Sajama, Alon Orlitsky
Semi-parametric Exponential Family PCA. NIPS (2004)

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Publication Activity (10 Years)

Top Topics

Top Venues

Alon Orlitsky