55 citations · 144 across the 19 of their papers we have counts for
28 papers
lifelines-hc: Higher Criticism testing for sparse non-proportional hazard departures in Python
Alon Kipnis, Ben Galili, Zohar Yakhini
The log-rank test is the standard tool for two-sample survival comparison and has good power against proportional-hazards alternatives, but it loses power against sparse hazard dep…
Why Constants Matter in Distribution Testing: From Uniformity to Calibration
Alon Kipnis
Distribution goodness-of-fit testing has developed a powerful rate-level theory: we often know how the required sample size scales with the alphabet size, the separation from the n…
Sharp Lower Bound on the Minimax Risk for Multinomial Uniformity Testing via a Conditional Central Limit Theorem
Alon Kipnis
We study minimax goodness-of-fit testing for uniformity from multinomial observations over categories against departures of size . Writing $u_n:=ε_n^2 n\,N^{3…
Robust Extended Kalman Filter for Land Navigation Using Massive Array of MEMS IMUs
Omer Hanani, Alon Kipnis
We propose a robust Extended Kalman Filter (EKF) architecture for land navigation using an array of hundreds of low-cost micro-electromechanical systems (MEMS) inertial sensors. Th…
Critical biblical studies via word frequency analysis: unveiling text authorship
Shira Faigenbaum-Golovin, Alon Kipnis, Axel Bühler +3
The Bible, a product of an extensive and intricate process of oral-written transmission spanning centuries, obscures the contours of its earlier recensions. Debate rages over deter…
Higher-criticism for sparse multi-stream change-point detection
Tingnan Gong, Alon Kipnis, Yao Xie
We study a statistical procedure based on higher criticism (HC) to address the sparse multi-stream quickest change-point detection problem. Namely, we aim to detect a potential cha…
Higher criticism for rare and weak non-proportional hazard deviations in survival analysis
Alon Kipnis, Ben Galili, Zohar Yakhini
We propose a method for comparing survival data based on the higher criticism of p-values obtained from multiple exact hypergeometric tests. The method accommodates non-informative…
EntropyRank: Unsupervised Keyphrase Extraction via Side-Information Optimization for Language Model-based Text Compression
Alexander Tsvetkov, Alon Kipnis
We propose an unsupervised method to extract keywords and keyphrases from texts based on a pre-trained language model (LM) and Shannon's information maximization. Specifically, our…
An Information-Theoretic Approach for Detecting Edits in AI-Generated Text
Idan Kashtan, Alon Kipnis
We propose a method to determine whether a given article was written entirely by a generative language model or perhaps contains edits by a different author, possibly a human. Our…
The Minimax Risk in Testing Uniformity over Large Alphabets under Missing-Ball Alternatives
Alon Kipnis
We study the problem of testing the goodness of fit of categorical count data to a Poisson distribution uniform over the categories, against a class of alternatives defined by excl…
The Impossibility Region for Detecting Sparse Mixtures using the Higher Criticism
David L. Donoho, Alon Kipnis
Consider a multiple hypothesis testing setting involving rare/weak effects: relatively few tests, out of possibly many, deviate from their null hypothesis behavior. Summarizing the…
Higher Criticism to Compare Two Large Frequency Tables, with sensitivity to Possible Rare and Weak Differences
David L. Donoho, Alon Kipnis
We adapt Higher Criticism (HC) to the comparison of two frequency tables which may -- or may not -- exhibit moderate differences between the tables in some unknown, relatively smal…
Gaussian Approximation of Quantization Error for Estimation from Compressed Data
Alon Kipnis, Galen Reeves
We consider the distributional connection between the lossy compressed representation of a high-dimensional signal using a random spherical code and the observation of unde…
Higher Criticism for Discriminating Word-Frequency Tables and Testing Authorship
Alon Kipnis
We adapt the Higher Criticism (HC) goodness-of-fit test to measure the closeness between word-frequency tables. We apply this measure to authorship attribution challenges, where th…
Mean Estimation from One-Bit Measurements
Alon Kipnis, John C. Duchi
We consider the problem of estimating the mean of a symmetric log-concave distribution under the constraint that only a single bit per sample from this distribution is available to…
Lossy Compression of Decimated Gaussian Random Walks
Georgia Murray, Alon Kipnis, Andrea J. Goldsmith
We consider the problem of estimating a Gaussian random walk from a lossy compression of its decimated version. Hence, the encoder operates on the decimated random walk, and the de…
Analog-to-Digital Compression: A New Paradigm for Converting Signals to Bits
Alon Kipnis, Yonina C. Eldar, Andrea J. Goldsmith
Processing, storing and communicating information that originates as an analog signal involves conversion of this information to bits. This conversion can be described by the combi…
Mean Estimation from Adaptive One-bit Measurements
Alon Kipnis, John C. Duchi
We consider the problem of estimating the mean of a normal distribution under the following constraint: the estimator can access only a single bit from each sample from this distri…
Compress-and-Estimate Source Coding for a Vector Gaussian Source
Ruiyang Song, Stefano Rini, Alon Kipnis +1
We consider the remote vector source coding problem in which a vector Gaussian source is to be estimated from noisy linear measurements. For this problem, we derive the performance…
The Distortion-Rate Function of Sampled Wiener Processes
Alon Kipnis, Andrea J. Goldsmith, Yonina C. Eldar
We consider the recovery of a continuous-time Wiener process from a quantized or lossy compressed version of its uniform samples under limited bitrate and sampling rate. We derive…
Optimal Rate Allocation in Mismatched Multiterminal Source Coding
Ruiyang Song, Stefano Rini, Alon Kipnis +1
We consider a multiterminal source coding problem in which a source is estimated at a central processing unit from lossy-compressed remote observations. Each lossy-encoded observat…
The Rate-Distortion Risk in Estimation from Compressed Data
Alon Kipnis, Stefano Rini, Andrea J. Goldsmith
Consider the problem of estimating a latent signal from a lossy compressed version of the data when the compressor is agnostic to the relation between the signal and the data. This…
Fundamental Distortion Limits of Analog-to-Digital Compression
Alon Kipnis, Yonina C. Eldar, Andrea J. Goldsmith
Representing a continuous-time signal by a set of samples is a classical problem in signal processing. We study this problem under the additional constraint that the samples are qu…
Indirect Rate-Distortion Function of a Binary i.i.d Source
Alon Kipnis, Stefano Rini, Andrea J. Goldsmith
The indirect source-coding problem in which a Bernoulli process is compressed in a lossy manner from its noisy observations is considered. These noisy observations are obtained by…