For a uniform random Boolean function on p bits, its low-degree Fourier coefficients uniquely determine it with high probability precisely when d exceeds p/2 by an O(sqrt(p log p)) window.
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Probability inequalities for sums of bounded random variables
17 Pith papers cite this work. Polarity classification is still indexing.
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Rigorous security proofs for variable-length QKD, phase-error bounding with imperfect detectors, marginal-constrained entropy accumulation, and authentication reductions place practical QKD on firmer mathematical ground.
S2-WEF detects dynamic free-riders in federated learning by simulating attack WEF patterns from prior global models, combining them with mutual deviation scores, and using two-dimensional clustering without proxy data or pre-training.
STE is a differentiable method to compute continuous analogues of the Top Cycle and Uncovered Set from pairwise comparison data for stable set-valued evaluation of cyclic agent interactions.
SVAR-FM uses simulator clamping to produce interventional distributions and flow matching to identify time series causal structures, with an error bound that predicts sign reversal of causal effects below a simulator accuracy threshold.
QESEM is a characterization-based error mitigation technique that achieves unbiased estimates with substantially reduced runtime cost compared to probabilistic error cancellation while outperforming zero-noise extrapolation on utility-scale circuits.
Two strategies are introduced for transmission over unknown binary erasure channels: a two-phase method achieving O(T^{2/3}) regret with one query and a windowing method achieving O(sqrt(T)) regret with O(log T) queries.
Proves PAC consistency and explicit convergence rates for learned transport integrated (LtI) quadrature using neural ODE flows for general targets and empirical quantile maps for product targets.
The authors give an Õ(n + √(wt))-time algorithm for Subset Sum.
Unifying framework for CTree, MOB and GUIDE shows model scores without dichotomization yield higher power for covariate selection than residuals or dichotomized scores in many scenarios.
Arqon delivers reliable quantum network service via admission control and scheduling that satisfies defined reliability requirements for accepted demands in static topologies, with O(k^3) and O(N^3) complexity.
A framework applies frequent itemset mining with the negFIN algorithm and unsupervised learning to identify cities sharing co-occurring land use patterns from Copernicus Urban Atlas data.
A model-free method builds confidence sets for latent parameters to proxy sim-to-real discrepancies and estimates the quantile function of that proxy to produce a distribution-level fidelity profile for simulators.
The paper introduces a modular, hardware-agnostic architecture using entanglement packets for scheduling network operations in quantum networks to enable end-to-end entanglement generation integrated with local program execution, demonstrated via simulation on a 6-node star topology.
For two orthogonal black-box n-qubit states, a poly(n, 1/ε)-size approximating unitary exists that maps basis states to them while resetting all auxiliaries on every input.
NPAP is a Python package built on NetworkX that supplies 13 partitioning strategies and two aggregation profiles for network graph reduction via a strategy pattern allowing custom extensions.
An unsupervised-to-supervised ML pipeline on UK NDNS data discovers four dietary patterns, reproduces them with macro-F1 0.963 using a surrogate classifier, and interprets them via SHAP for potential clinical use.
citing papers explorer
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Low-Degree Fourier Threshold for Random Boolean Functions
For a uniform random Boolean function on p bits, its low-degree Fourier coefficients uniquely determine it with high probability precisely when d exceeds p/2 by an O(sqrt(p log p)) window.
-
Rigorous Security Proofs for Practical Quantum Key Distribution
Rigorous security proofs for variable-length QKD, phase-error bounding with imperfect detectors, marginal-constrained entropy accumulation, and authentication reductions place practical QKD on firmer mathematical ground.
-
Dynamic Free-Rider Detection in Federated Learning via Simulated Attack Patterns
S2-WEF detects dynamic free-riders in federated learning by simulating attack WEF patterns from prior global models, combining them with mutual deviation scores, and using two-dimensional clustering without proxy data or pre-training.
-
Soft Tournament Equilibrium
STE is a differentiable method to compute continuous analogues of the Top Cycle and Uncovered Set from pairwise comparison data for stable set-valued evaluation of cyclic agent interactions.
-
Intervention-Based Time Series Causal Discovery via Simulator-Generated Interventional Distributions
SVAR-FM uses simulator clamping to produce interventional distributions and flow matching to identify time series causal structures, with an error bound that predicts sign reversal of causal effects below a simulator accuracy threshold.
-
Reliable high-accuracy error mitigation for utility-scale quantum circuits
QESEM is a characterization-based error mitigation technique that achieves unbiased estimates with substantially reduced runtime cost compared to probabilistic error cancellation while outperforming zero-noise extrapolation on utility-scale circuits.
-
Learning to Transmit Over Unknown Erasure Channels with Empirical Erasure Rate Feedback
Two strategies are introduced for transmission over unknown binary erasure channels: a two-phase method achieving O(T^{2/3}) regret with one query and a windowing method achieving O(sqrt(T)) regret with O(log T) queries.
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Consistency of Learned Sparse Grid Quadrature Rules using NeuralODEs
Proves PAC consistency and explicit convergence rates for learned transport integrated (LtI) quadrature using neural ODE flows for general targets and empirical quantile maps for product targets.
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An Improved Pseudopolynomial Time Algorithm for Subset Sum
The authors give an Õ(n + √(wt))-time algorithm for Subset Sum.
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The Power of Unbiased Recursive Partitioning: A Unifying View of CTree, MOB, and GUIDE
Unifying framework for CTree, MOB and GUIDE shows model scores without dichotomization yield higher power for covariate selection than residuals or dichotomized scores in many scenarios.
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Arqon: A suite of control applications enabling a reliable quantum network
Arqon delivers reliable quantum network service via admission control and scheduling that satisfies defined reliability requirements for accepted demands in static topologies, with O(k^3) and O(N^3) complexity.
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Exploring Urban Land Use Patterns by Pattern Mining and Unsupervised Learning
A framework applies frequent itemset mining with the negFIN algorithm and unsupervised learning to identify cities sharing co-occurring land use patterns from Copernicus Urban Atlas data.
-
Model-Free Assessment of Simulator Fidelity via Quantile Curves
A model-free method builds confidence sets for latent parameters to proxy sim-to-real discrepancies and estimates the quantile function of that proxy to produce a distribution-level fidelity profile for simulators.
-
A Modular Quantum Network Architecture for Integrating Network Scheduling with Local Program Execution
The paper introduces a modular, hardware-agnostic architecture using entanglement packets for scheduling network operations in quantum networks to enable end-to-end entanglement generation integrated with local program execution, demonstrated via simulation on a 6-node star topology.
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Approximating Unitary Preparations of Orthogonal Black Box States
For two orthogonal black-box n-qubit states, a poly(n, 1/ε)-size approximating unitary exists that maps basis states to them while resetting all auxiliaries on every input.
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NPAP: Network Partitioning and Aggregation Package for Python
NPAP is a Python package built on NetworkX that supplies 13 partitioning strategies and two aggregation profiles for network graph reduction via a strategy pattern allowing custom extensions.
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An Explainable Unsupervised-to-Supervised Machine Learning Framework for Dietary Pattern Discovery Using UK National Dietary Survey Data
An unsupervised-to-supervised ML pipeline on UK NDNS data discovers four dietary patterns, reproduces them with macro-F1 0.963 using a surrogate classifier, and interprets them via SHAP for potential clinical use.