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cs.DS updates on arXiv.org

PAC Learning with Bandit Feedback: Sharp Sample Complexity in the Realizable Setting Algorithms with Polynomially-Improved Approximation Factors for the $2 \rightarrow q$ Norm, and Applications A computational phase transition for learning-to-sample from Ising models Covering vertices by sequential stars Fermi-Dirac machines as quantizations of neurons A Comprehensive Evaluation of Vertex Elimination Algorithms for Algorithmic Differentiation A Tight Bound on Localization of Electrical Flows Optimal Dimension-Free Sampling for Regularized Classification Reducing the Randomness in Partition Oracles for Bounded Degree Minor-Free Graphs Beyond the Half-Approximation: Fair and Efficient Online Class Matching Efficient Uniform Sampling of Surjections via their Profiles Tractable Maximization of Budgeted Phylogenetic Diversity on Networks Utilizing Node Scanwidth Fairness in Aggregation: Optimal Top-$k$ and Improved Full Ranking Learning-Augmented Online Scheduling with Parsimonious Preemption Entropy Equivalence Testing Lumberjack: Better Differentially Private Random Forests through Heavy Hitter Detection in Trees The Secretary Problem with a Stochastic Precursor Polynomial-Time Robust Multiclass Linear Classification under Gaussian Marginals Efficient Banzhaf-Based Data Valuation for $k$-Nearest Neighbors Classification Block-Sphere Vector Quantization An Approximation Algorithm for Graph Label Selection Iterative Chow Filtering for Learning with Distribution Shift Complexity of Non-Log-Concave Sampling in Fisher Information Stochastic Matching via Local Sparsification Finite Sample Bounds for Learning with Score Matching What is Learnable in Valiant's Theory of the Learnable? Provable Quantization with Randomized Hadamard Transform Min-Max Optimization Requires Exponentially Many Queries Fast and Compact Graph Cuts for the Boykov-Kolmogorov Algorithm A proximal gradient algorithm for composite log-concave sampling
An Algorithm and Estimates for the Erdős-Selfridge Functi...
Brianna Sorenson, Jonathan P Sorenson, Jonathan Webster · 2019-07-20 · via cs.DS updates on arXiv.org

Let $p(n)$ denote the smallest prime divisor of the integer $n$. Define the function $g(k)$ to be the smallest integer $>k+1$ such that $p(\binom{g(k)}{k})>k$. So we have $g(2)=6$ and $g(3)=g(4)=7$. In this paper we present the following new results on the Erdős-Selfridge function $g(k)$: We present a new algorithm to compute the value of $g(k)$, and use it to both verify previous work and compute new values of $g(k)$, with our current limit being $$ g(323)= 1\ 69829\ 77104\ 46041\ 21145\ 63251\ 22499. $$ We define a new function $\hat{g}(k)$, and under the assumption of our Uniform Distribution Heuristic we show that $$ \log g(k) = \log \hat{g}(k) + O(\log k) $$ with high "probability". We also provide computational evidence to support our claim that $\hat{g}(k)$ estimates $g(k)$ reasonably well in practice. There are several open conjectures on the behavior of $g(k)$ which we are able to prove for $\hat{g}(k)$, namely that $$ 0.525\ldots +o(1) \quad \le \quad \frac{\log \hat{g}(k)}{k/\log k} \quad \le \quad 1+o(1), $$ and that $$ \limsup_{k\rightarrow\infty} \frac{\hat{g}(k+1)}{\hat{g}(k)}=\infty.$$ Let $G(x,k)$ count the number of integers $n\le x$ such that $p(\binom{n}{k})>k$. Unconditionally, we prove that for large $x$, $G(x,k)$ is asymptotic to $x/\hat{g}(k)$. And finally, we show that the running time of our new algorithm is at most $g(k) \exp[ -c (k\log\log k) /(\log k)^2 (1+o(1))]$ for a constant $c>0$.