Sandeep Silwal

According to our database1, Sandeep Silwal authored at least 32 papers between 2018 and 2024.

Collaborative distances:
  • Dijkstra number2 of three.
  • Erdős number3 of two.

Timeline

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Bibliography

2024
Efficiently Computing Similarities to Private Datasets.
CoRR, 2024

2023
Improved Space Bounds for Learning with Experts.
CoRR, 2023

KwikBucks: Correlation Clustering with Cheap-Weak and Expensive-Strong Signals.
Proceedings of The Fourth Workshop on Simple and Efficient Natural Language Processing, 2023

Optimal Algorithms for Linear Algebra in the Current Matrix Multiplication Time.
Proceedings of the 2023 ACM-SIAM Symposium on Discrete Algorithms, 2023

Near-Linear Time Algorithm for the Chamfer Distance.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Improved Frequency Estimation Algorithms with and without Predictions.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Constant Approximation for Individual Preference Stable Clustering.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Data Structures for Density Estimation.
Proceedings of the International Conference on Machine Learning, 2023

Robust Algorithms on Adaptive Inputs from Bounded Adversaries.
Proceedings of the Eleventh International Conference on Learning Representations, 2023

Subquadratic Algorithms for Kernel Matrices via Kernel Density Estimation.
Proceedings of the Eleventh International Conference on Learning Representations, 2023

Learned Interpolation for Better Streaming Quantile Approximation with Worst-Case Guarantees.
Proceedings of the SIAM Conference on Applied and Computational Discrete Algorithms, 2023

2022
A concentration inequality for the facility location problem.
Oper. Res. Lett., 2022

Sub-quadratic Algorithms for Kernel Matrices via Kernel Density Estimation.
CoRR, 2022

The White-Box Adversarial Data Stream Model.
Proceedings of the PODS '22: International Conference on Management of Data, Philadelphia, PA, USA, June 12, 2022

Faster Linear Algebra for Distance Matrices.
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Learning-Augmented Algorithms for Online Linear and Semidefinite Programming.
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Exponentially Improving the Complexity of Simulating the Weisfeiler-Lehman Test with Graph Neural Networks.
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Faster Fundamental Graph Algorithms via Learned Predictions.
Proceedings of the International Conference on Machine Learning, 2022

Hardness and Algorithms for Robust and Sparse Optimization.
Proceedings of the International Conference on Machine Learning, 2022

Learning-Augmented $k$-means Clustering.
Proceedings of the Tenth International Conference on Learning Representations, 2022

Triangle and Four Cycle Counting with Predictions in Graph Streams.
Proceedings of the Tenth International Conference on Learning Representations, 2022

Motif Cut Sparsifiers.
Proceedings of the 63rd IEEE Annual Symposium on Foundations of Computer Science, 2022

2021
Dimensionality Reduction for Wasserstein Barycenter.
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Adversarial Robustness of Streaming Algorithms through Importance Sampling.
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Randomized Dimensionality Reduction for Facility Location and Single-Linkage Clustering.
Proceedings of the 38th International Conference on Machine Learning, 2021

Learning-based Support Estimation in Sublinear Time.
Proceedings of the 9th International Conference on Learning Representations, 2021

Smoothed Analysis of the Condition Number Under Low-Rank Perturbations.
Proceedings of the Approximation, 2021

2020
Testing Properties of Multiple Distributions with Few Samples.
Proceedings of the 11th Innovations in Theoretical Computer Science Conference, 2020

Property Testing of LP-Type Problems.
Proceedings of the 47th International Colloquium on Automata, Languages, and Programming, 2020

2019
Using Dimensionality Reduction to Optimize t-SNE.
CoRR, 2019

Directed random geometric graphs.
J. Complex Networks, 2019

2018
Spectral methods for testing cluster structure of graphs.
CoRR, 2018


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