Keyphrases
Approximate Nearest Neighbor Search
24%
Approximation Algorithms
55%
Approximation Factor
48%
Better Approximation
24%
Bipartite Graph
28%
Connected Matchings
24%
Constant Approximation
30%
Data-driven Algorithm
48%
Dimensionality Reduction
42%
Eccentricity
48%
Euclidean Metric
48%
Fair Clustering
48%
Fast Nearest Neighbor Search
32%
Fast-moving
48%
Few-shot
24%
Graph Stream
24%
Hardness Results
33%
High Dimension
32%
High-dimensional Data
32%
K-median
48%
K-nearest Neighbor (K-NN)
63%
Kernel Density Estimation
55%
Label Propagation
48%
Learning-based
30%
Log-log
24%
Logging System
24%
Low-rank Approximation
55%
Metric Compression
73%
Near-optimal
30%
Nearest Neighbor Search
73%
Network Architecture
24%
Neural Network
47%
Optimal Transport
48%
Popular
44%
Quantile Approximation
24%
Query Point
36%
Sample Complexity
30%
Scalable Machine Learning
24%
Semi-supervised Learning
48%
Semi-supervised Learning Algorithm
48%
Set Cover
28%
Streaming Algorithms
40%
Sublinear Time
28%
Support Estimation
24%
System Administrator
24%
Temporal Labels
48%
Tight
36%
Training Time
24%
Wasserstein Distance
48%
Worst-Case Guarantees
24%
Computer Science
Approximation (Algorithm)
69%
Approximation Algorithms
28%
approximation factor
40%
Approximation Technique
24%
Bipartite Graph
30%
Computational Bottleneck
16%
Computational Modeling
32%
Computer System
24%
Data Domain
16%
Data Stream
73%
Density Function
24%
Differential Privacy
24%
Dimensional Data
24%
Dimensional Data Set
12%
Dimensional Space
12%
Distance Matrix
24%
Efficient Algorithm
24%
Estimation Accuracy
24%
Estimation Algorithm
24%
Experimental Result
55%
Feature Vector
14%
Gaussian Kernel
48%
Graph Neural Network
24%
Graph Theory
12%
High Dimensional Data
24%
Labeled Example
48%
Large Data Set
57%
Learning Algorithm
24%
Learning Space
24%
Learning System
24%
Locality Sensitive Hashing
36%
Log Management System
24%
Machine Learning
32%
Massive Datasets
16%
Multitasking
48%
Neighbour Search
73%
Neural Network
45%
Preprocessing Time
24%
Product Quantization
24%
Rank Approximation
48%
Run-to-Completion
12%
Searching Algorithm
38%
Semisupervised Learning
48%
Space Complexity
22%
Sparsity
48%
Subgraphs
24%
System Administrator
24%
Theoretic Approach
24%
User Data
24%
Vector Multiplication
24%
Mathematics
Approximates
100%
Bipartite Graph
24%
Closest Pair
24%
Clustering
36%
Complexity Space
28%
Data Structure
61%
Decomposition Algorithms
18%
Density Estimation
24%
Dependent Data
24%
Dimensional Space
36%
Dimensionality Reduction
61%
Distance Matrix
24%
Distinct Element
24%
Edge
87%
Eigenvalue
16%
Expander
24%
Fast Algorithm
13%
Gaussian Distribution
17%
Higher Dimensions
24%
Histogram
24%
Kernel Density Estimation
32%
Laplace Operator
12%
Lindenstrauss
61%
Linear Space
12%
Linear Time
18%
Low-Rank Approximation
32%
Lower and upper bounds
20%
Main Result
44%
Matching Problem
16%
Matrix (Mathematics)
73%
Matrix Algebra
24%
Matrix-Vector Multiplication
24%
Median
48%
Minimizes
18%
Nearest Neighbor
24%
Neural Network
48%
Numerical Linear Algebra
24%
Polynomial Time
24%
Property Testing
24%
Quantile
24%
Random Sample
24%
Real-World Data
12%
Relative Error
16%
Running Time
30%
Set Point
18%
Set Size
24%
Triangle
24%
Unstructured Text
24%
Upper Bound
14%
Worst Case
29%
