
Graph Homomorphism Convolution
In this paper, we study the graph classification problem from the graph ...
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Tightly Robust Optimization via Empirical Domain Reduction
Datadriven decisionmaking is performed by solving a parameterized opti...
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Learning Directly from Grammar Compressed Text
Neural networks using numerous text data have been successfully applied ...
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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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Empirical Hypothesis Space Reduction
Selecting appropriate regularization coefficients is critical to perform...
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Multiple KnapsackConstrained Monotone DRSubmodular Maximization on Distributive Lattice  Continuous Greedy Algorithm on Median Complex 
We consider a problem of maximizing a monotone DRsubmodular function un...
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rGather Clustering and rGathering on Spider: FPT Algorithms and Hardness
We consider minmax rgather clustering problem and minmax rgathering ...
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PTAS and Exact Algorithms for rGathering Problems on Tree
rgathering problem is a variant of facility location problems. In this ...
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Stochastic Monotone Submodular Maximization with Queries
We study a stochastic variant of monotone submodular maximization proble...
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Data Cleansing for Models Trained with SGD
Data cleansing is a typical approach used to improve the accuracy of mac...
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Revisiting Graph Neural Networks: All We Have is LowPass Filters
Graph neural networks have become one of the most important techniques t...
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Incorrect implementations of the FloydWarshall algorithm give correct solutions after three repeats
The FloydWarshall algorithm is a wellknown algorithm for the allpair...
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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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Pretending Fair Decisions via Stealthily Biased Sampling
Fairness by decisionmakers is believed to be auditable by third parties...
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Convex Hull Approximation of Nearly Optimal Lasso Solutions
In an ordinary feature selection procedure, a set of important features ...
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A Simple Way to Deal with Cherrypicking
Statistical hypothesis testing serves as statistical evidence for scient...
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Submodular Stochastic Probing with Prices
We introduce Stochastic Probing with Prices (SPP), a variant of the Stoc...
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Linear PseudoPolynomial Factor Algorithm for Automaton Constrained Tree Knapsack Problem
The automaton constrained tree knapsack problem is a variant of the knap...
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Algorithmic MetaTheorems for Monotone Submodular Maximization
We consider a monotone submodular maximization problem whose constraint ...
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Maximally Invariant Data Perturbation as Explanation
While several feature scoring methods are proposed to explain the output...
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Subspace Selection via DRSubmodular Maximization on Lattices
The subspace selection problem seeks a subspace that maximizes an object...
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ClassiNet  Predicting Missing Features for ShortText Classification
The fundamental problem in shorttext classification is feature sparsene...
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Neural Photometric Stereo Reconstruction for General Reflectance Surfaces
We present a novel convolutional neural network architecture for photome...
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On Tensor Train Rank Minimization: Statistical Efficiency and Scalable Algorithm
Tensor train (TT) decomposition provides a spaceefficient representatio...
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Finding Alternate Features in Lasso
We propose a method for finding alternate features missing in the Lasso ...
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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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Embedding Semantic Relations into Word Representations
Learning representations for semantic relations is important for various...
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Learning Word Representations from Relational Graphs
Attributes of words and relations between two words are central to numer...
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Takanori Maehara
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