DOCSLIB.ORG
Explore
Sign Up
Log In
Upload
Search
Home
» Tags
» Count sketch
Count sketch
Short and Deep: Sketching and Neural Networks
Lsh)
Fast and Scalable Polynomial Kernels Via Explicit Feature Maps *
Learning-Based Frequency Estimation Algorithms
Incremental Randomized Sketching for Online Kernel Learning
Compressing Gradient Optimizers Via Count-Sketches
Communication-Efficient Federated Learning with Sketching
Tensors in Modern Statistical Learning 1 Introduction
(Learned) Frequency Estimation Algorithms Under Zipfian Distribution
Communication-Efficient Distributed SGD with Sketching
Privacy for Free: Communication-Efficient Learning
Frequency Estimation in Data Streams: Learning the Optimal Hashing Scheme
Question Type Guided Attention in Visual Question Answering
Finding Heavily-Weighted Features with the Weight-Median Sketch
Higher-Order Count Sketch: Dimensionality Reduction That Retains Efficient Tensor Operations
NIPS 2018 Workshop Book Generated Thu Mar 07, 2019
Arxiv:1804.02088V2 [Cs.CV] 18 Jul 2018
Enhancing the Privacy of Federated Learning with Sketching
Top View
Discriminative and Dynamic Similarity-Preserving Sketching of Streaming Histograms
Contextual Models for Sequential Recommendation
Streaming, Sketching and Sufficient Statistics (Slides)
Multimodal Deep Learning Methods for Person Annotation in Video Sequences
Count-Based Frequency Estimation with Bounded Memory
Almost Optimal Tensor Sketch
Building and Evaluating Privacy-Preserving Data Processing Systems
Proposed Course Syllabus
Arxiv:1904.01790V2 [Cs.LG] 14 Apr 2019 Etr Xrcin Enocmn Erighsas Benefi Also Has Learning F (DQN) Reinforcement Complex Network More Allowed Extraction
Multi-Dimensional Tensor Sketch: Dimensionality Reduction That Retains Efficient Tensor Operations
Finite Sample Analysis of LSTD with Random Projections and Eligibility Traces
Efficient Tensor Operations Via Compression and Parallel Computation
Sketching Linear Classifiers Over Data Streams
Effective Sketching Methods for Value Function Approximation
Quantum Circuit-Like Learning: a Fast and Scalable Classical Machine-Learning Algorithm with Similar Performance to Quantum Circuit Learning
Arxiv:1812.09489V1 [Cs.LG] 22 Dec 2018 Prof
Enhancing Selectivity in Big Data
Communication-Efficient Distributed SGD with Sketching
Fast and Guaranteed Tensor Decomposition Via Sketching
Learning-Based Frequency Estimation Algorithms
Compressing Gradient Optimizers Via Count-Sketches
Efficient Methods for Prediction and Control in Partially Observable
Effective Sketching Methods for Value Function Approximation
Fetchsgd: Communication-Efficient Federated Learning with Sketching