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Approximation Algorithms

110 papers

Papers per year

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Papers

Near Optimal Reconstruction of Spherical Harmonic Expansions NIPS 2023
Replicable Clustering NIPS 2023
Composable Coresets for Determinant Maximization: Greedy is Almost Optimal NIPS 2023
Fair, Polylog-Approximate Low-Cost Hierarchical Clustering NIPS 2023
Sketching Algorithms for Sparse Dictionary Learning: PTAS and Turnstile Streaming NIPS 2023
A Learnable Radial Basis Positional Embedding for Coordinate-MLPs AAAI 2023
Submodular Maximization under the Intersection of Matroid and Knapsack Constraints AAAI 2023
An Improved Approximation Algorithm for Wage Determination and Online Task Allocation in Crowd-Sourcing AAAI 2023
Optimizing Multiple Simultaneous Objectives for Voting and Facility Location AAAI 2023
Multi-Stage Facility Location Problems with Transient Agents AAAI 2023
Truthful Mechanisms for Steiner Tree Problems AAAI 2023
Reconstructing an Epidemic Outbreak Using Steiner Connectivity AAAI 2023
A Faster Practical Approximation Scheme for the Permanent AAAI 2023
Approximation Algorithms for Fair Range Clustering ICML 2023
Generic bounds on the approximation error for physics-informed (and) operator learning NIPS 2022
Statistically Meaningful Approximation: a Case Study on Approximating Turing Machines with Transformers NIPS 2022
Efficient Submodular Optimization under Noise: Local Search is Robust NIPS 2022
A Differentially Private Linear-Time fPTAS for the Minimum Enclosing Ball Problem NIPS 2022
Recruitment Strategies That Take a Chance NIPS 2022
Learning-Augmented Algorithms for Online Linear and Semidefinite Programming NIPS 2022
Parameterized Approximation Algorithms for K-center Clustering and Variants AAAI 2022
Dimensionality and Coordination in Voting: The Distortion of STV AAAI 2022
Generalized Stochastic Matching AAAI 2022
Large-Scale Learning with Fourier Features and Tensor Decompositions NIPS 2021
Fair Scheduling for Time-dependent Resources NIPS 2021