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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
Bipartitioning Problems on Graphs with Bounded Tree-Width
N. R. Aravind, Subrahmanyam Kalyanasundaram, Anjeneya Swami Kare · 2018-04-11 · via cs.DS updates on arXiv.org

For an undirected graph G, we consider the following problems: given a fixed graph H, can we partition the vertices of G into two non-empty sets A and B such that neither the induced graph G[A] nor G[B] contain H (i) as a subgraph? (ii) as an induced subgraph? These problems are NP-complete and are expressible in monadic second order logic (MSOL). The MSOL formulation, together with Courcelle's theorem implies linear time solvability on graphs with bounded tree-width. This approach yields algorithms with running time f(|phi|, t) * n, where |phi| is the length of the MSOL formula, t is the tree-width of the graph and n is the number of vertices of the graph. The dependency of f(|phi|, t) on |phi| can be as bad as a tower of exponentials. In this paper, we present explicit combinatorial algorithms for these problems for graphs G whose tree-width is bounded. We obtain 2^{O(t^r)} * n time algorithms when H is any fixed graph of order r. In the special case when H = K_r, a complete graph on r vertices, we get an 2^{O(t+r \log t)} * n time algorithm. The techniques can be extended to provide FPT algorithms to determine the smallest number q such that V can be partitioned into q parts such that none of the parts have H as a subgraph (induced subgraph).