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11/05/2021
Learning on Random Balls is Sufficient for Estimating (Some) Graph Parameters
Theoretical analyses for graph learning methods often assume a complete ...
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02/24/2021
Abelian Neural Networks
We study the problem of modeling a binary operation that satisfies some ...
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12/05/2020
r-Gathering Problems on Spiders:Hardness, FPT Algorithms, and PTASes
We consider the min-max r-gathering problem described as follows: We are...
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11/22/2020
Stacked Graph Filter
We study Graph Convolutional Networks (GCN) from the graph signal proces...
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05/03/2020
Graph Homomorphism Convolution
In this paper, we study the graph classification problem from the graph ...
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02/29/2020
Tightly Robust Optimization via Empirical Domain Reduction
Data-driven decision-making is performed by solving a parameterized opti...
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02/28/2020
Learning Directly from Grammar Compressed Text
Neural networks using numerous text data have been successfully applied ...
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10/09/2019
A Simple Proof of the Universality of Invariant/Equivariant Graph Neural Networks
We present a simple proof for the universality of invariant and equivari...
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09/04/2019
Empirical Hypothesis Space Reduction
Selecting appropriate regularization coefficients is critical to perform...
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07/09/2019
Multiple Knapsack-Constrained Monotone DR-Submodular Maximization on Distributive Lattice --- Continuous Greedy Algorithm on Median Complex ---
We consider a problem of maximizing a monotone DR-submodular function un...
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07/09/2019
r-Gather Clustering and r-Gathering on Spider: FPT Algorithms and Hardness
We consider min-max r-gather clustering problem and min-max r-gathering ...
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07/09/2019
PTAS and Exact Algorithms for r-Gathering Problems on Tree
r-gathering problem is a variant of facility location problems. In this ...
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07/09/2019
Stochastic Monotone Submodular Maximization with Queries
We study a stochastic variant of monotone submodular maximization proble...
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06/20/2019
Data Cleansing for Models Trained with SGD
Data cleansing is a typical approach used to improve the accuracy of mac...
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05/23/2019
Revisiting Graph Neural Networks: All We Have is Low-Pass Filters
Graph neural networks have become one of the most important techniques t...
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04/02/2019
Incorrect implementations of the Floyd--Warshall algorithm give correct solutions after three repeats
The Floyd--Warshall algorithm is a well-known algorithm for the all-pair...
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02/23/2019
Optimal Algorithm to Reconstruct a Tree from a Subtree Distance
This paper addresses the problem of finding a representation of a subtre...
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01/24/2019
Pretending Fair Decisions via Stealthily Biased Sampling
Fairness by decision-makers is believed to be auditable by third parties...
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10/14/2018
Convex Hull Approximation of Nearly Optimal Lasso Solutions
In an ordinary feature selection procedure, a set of important features ...
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10/11/2018
A Simple Way to Deal with Cherry-picking
Statistical hypothesis testing serves as statistical evidence for scient...
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10/03/2018
Submodular Stochastic Probing with Prices
We introduce Stochastic Probing with Prices (SPP), a variant of the Stoc...
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07/13/2018
Linear Pseudo-Polynomial Factor Algorithm for Automaton Constrained Tree Knapsack Problem
The automaton constrained tree knapsack problem is a variant of the knap...
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07/12/2018
Algorithmic Meta-Theorems for Monotone Submodular Maximization
We consider a monotone submodular maximization problem whose constraint ...
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06/19/2018
Maximally Invariant Data Perturbation as Explanation
While several feature scoring methods are proposed to explain the output...
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05/18/2018
Subspace Selection via DR-Submodular Maximization on Lattices
The subspace selection problem seeks a subspace that maximizes an object...
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04/14/2018
ClassiNet -- Predicting Missing Features for Short-Text Classification
The fundamental problem in short-text classification is feature sparsene...
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02/28/2018
Neural Photometric Stereo Reconstruction for General Reflectance Surfaces
We present a novel convolutional neural network architecture for photome...
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08/01/2017
On Tensor Train Rank Minimization: Statistical Efficiency and Scalable Algorithm
Tensor train (TT) decomposition provides a space-efficient representatio...
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11/18/2016
Finding Alternate Features in Lasso
We propose a method for finding alternate features missing in the Lasso ...
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11/19/2015
Joint Word Representation Learning using a Corpus and a Semantic Lexicon
Methods for learning word representations using large text corpora have ...
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05/01/2015
Embedding Semantic Relations into Word Representations
Learning representations for semantic relations is important for various...
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12/07/2014
