惯性聚合 高效追踪和阅读你感兴趣的博客、新闻、科技资讯
阅读原文 在惯性聚合中打开

推荐订阅源

MongoDB | Blog
MongoDB | Blog
宝玉的分享
宝玉的分享
博客园 - 三生石上(FineUI控件)
小众软件
小众软件
罗磊的独立博客
让小产品的独立变现更简单 - ezindie.com
让小产品的独立变现更简单 - ezindie.com
钛媒体:引领未来商业与生活新知
钛媒体:引领未来商业与生活新知
S
SegmentFault 最新的问题
Last Week in AI
Last Week in AI
人人都是产品经理
人人都是产品经理
博客园 - 聂微东
博客园 - 司徒正美
博客园 - 叶小钗
T
Tailwind CSS Blog
博客园 - Franky
V
V2EX
有赞技术团队
有赞技术团队
美团技术团队
雷峰网
雷峰网
爱范儿
爱范儿
Jina AI
Jina AI
D
DataBreaches.Net
H
Help Net Security
酷 壳 – CoolShell
酷 壳 – CoolShell

math updates on arXiv.org

Coupling-Robust Accuracy in Multiphysics Physics Informed Neural Networks via Kronecker-Preconditioned Optimization Non-normal spectral signatures of instability in neural network training dynamics Optimization of randomized neural networks for transfer operator approximation Selective Ambulance Dispatch Under Contextual Travel-Time Uncertainty LLAMA LIMA: A Living Meta-Analysis on the Effects of Generative AI on Learning Mathematics Neural Flow Operators can Approximate any Operator: Abstract Frameworks and Universal Approximations LLMs as Noisy Channels: A Shannon Perspective on Model Capacity and Scaling Laws On the Stability of Spherical Hellinger-Kantorovich Flows and Their Implications for Differential Privacy Training-Free Looped Transformers Move on Muon : A Hamiltonian probability gradient flow perspective of Muon optimizer Entrywise Error Bounds for Spectral Ranking with Semi-Random Adversaries Asymmetric Scaling Laws from Sparse Features Is Dimensionality a Barrier for Retrieval Models? RA-DCA: A Randomized Active-Set DCA for Directional Stationarity in Max-Structured DC Programs Commutator-Induced Uncertainty in VAEs Weisfeiler-Leman Is Incomplete on Simple Spectrum Graphs, so Canonicalize Them Sparse In-Network Learning via Shortest-Path Backpropagation and Finite-Rate Gating Instance-Optimal Estimation with Multiple LLM Judges on a Budget Entropy Equivalence Testing Expand More, Shrink Less: Shaping Effective-Rank Dynamics for Dense Scaling in Recommendation Any-Dimensional Invariant Universality Operationalizing Individual Fairness via Gradient Descent and Bradley-Terry Models Anytime Training with Schedule-Free Spectral Optimization Diffusion-based Denoising Beats Vanilla Score Matching in Parameter Estimation: A Theoretical Explanation Resilience Characterization of AI-Native Wireless Receivers via Persistent Homology The General Theory of Localization Methods Group-Algebraic Tensors: Provably-optimal Equivariant Learning and Physical Symmetry Discovery General Lower Bounds for Differentially Private Federated Learning with Arbitrary Public-Transcript Interactions PilotWiMAE: Pilot-Native Representation Learning for Wireless Channels Proximal basin hopping: global optimization with guarantees
Some results on Kleitman's conjecture
Jonathan Cary · 2024-02-06 · via math updates on arXiv.org

Chvátal conjectured that amongst the largest intersecting subfamilies of a finite subset-closed family of sets is a star. Kleitman later strengthened Chvátal's conjecture, defining a partial ordering on the vector space freely generated by $2^{[n]}$ and suggesting that the vector of every maximal intersecting subfamily of $2^{[n]}$ is bigger than a convex combination of stars. We restate Kleitman's conjecture in terms of the cochain complex of the discrete cube, studying it with techniques from convex optimization.