What is he best known for?
The fields of study he is best known for:
- Artificial intelligence
- Computer network
- Algorithm
The scientist’s investigation covers issues in Data mining, Differential privacy, Database, Correctness and Information retrieval.
His Data mining study incorporates themes from Histogram, Noise and Theoretical computer science.
His studies in Differential privacy integrate themes in fields like Point and Focus.
Yin Yang has researched Database in several fields, including Overhead, Range query and Search engine indexing.
In Search engine indexing, he works on issues like Object, which are connected to Task.
His research investigates the connection with Information retrieval and areas like World Wide Web which intersect with concerns in Semantic data model.
His most cited work include:
- Functional mechanism: regression analysis under differential privacy (197 citations)
- Heavy Hitter Estimation over Set-Valued Data with Local Differential Privacy (174 citations)
- Differentially private histogram publication (155 citations)
What are the main themes of his work throughout his whole career to date?
His primary scientific interests are in Data mining, Differential privacy, Theoretical computer science, Search engine indexing and Artificial neural network.
His Data mining research incorporates themes from Algorithm, Noise, Focus and Cluster analysis.
His Differential privacy research includes elements of Optimization problem, Information privacy and Query optimization.
In the subject of general Theoretical computer science, his work in PageRank is often linked to Node and Rank, thereby combining diverse domains of study.
His Search engine indexing research includes themes of Overhead, Database, Correctness, k-nearest neighbors algorithm and Computation.
His studies examine the connections between Database and genetics, as well as such issues in Data stream mining, with regards to Tuple.
He most often published in these fields:
- Data mining (24.55%)
- Differential privacy (23.64%)
- Theoretical computer science (18.18%)
What were the highlights of his more recent work (between 2019-2021)?
- Artificial neural network (11.82%)
- Memristor (8.18%)
- Computer engineering (4.55%)
In recent papers he was focusing on the following fields of study:
His primary areas of investigation include Artificial neural network, Memristor, Computer engineering, Convolutional neural network and Theoretical computer science.
In his study, Optimal control and Dynamic programming is inextricably linked to Nonlinear system, which falls within the broad field of Artificial neural network.
As part of the same scientific family, Yin Yang usually focuses on Computer engineering, concentrating on Categorization and intersecting with Model compression and State.
His Convolutional neural network research is multidisciplinary, relying on both Kernel and Computer vision.
His work in Theoretical computer science addresses issues such as Correctness, which are connected to fields such as Similarity.
His Cluster analysis research focuses on Solver and how it relates to Algorithm and Scalability.
Between 2019 and 2021, his most popular works were:
- Compressing Large-Scale Transformer-Based Models: A Case Study on BERT (35 citations)
- Memristor-Based Design of Sparse Compact Convolutional Neural Network (31 citations)
- Multilabel Image Classification via Feature/Label Co-Projection (29 citations)
In his most recent research, the most cited papers focused on:
- Artificial intelligence
- Computer network
- Algorithm
His primary areas of study are Computer engineering, Artificial neural network, Memristor, Algorithm and Convolutional neural network.
His Computer engineering research incorporates elements of Encoding, Transformer, Categorization, Sigmoid function and Activation function.
His research integrates issues of Upper and lower bounds, Hamilton–Jacobi–Bellman equation, Nonlinear system and Kernel in his study of Artificial neural network.
His Memristor research incorporates elements of Convolution, Distribution, Value and Layer.
His studies deal with areas such as Embedding, Pairwise comparison, Feature vector and PageRank as well as Algorithm.
The study incorporates disciplines such as Pooling, Pruning and Deep neural networks in addition to Convolutional neural network.
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