Saeed Reza Aghabozorgi
Artificial Intelligence · 2014–2015
A researcher in the Science corpus: 4 papers; trusts 53 researchers and is trusted by 10 researchers here, as inferred from the citation graph.
Subfields
- Artificial Intelligence — 70 citations into it; #15,188 of 35,345 by trust here, #14,181 by citations
- Signal Processing — 33 citations into it; #5,898 of 7,572 by trust here, #5,086 by citations
- Economics and Econometrics — 28 citations into it; #14,403 of 23,481 by trust here, #13,596 by citations
- Finance — 25 citations into it
- Information Systems — 25 citations into it
- Management Science and Operations Research — 22 citations into it; #5,841 of 11,946 by trust here, #3,977 by citations
- Computer Vision and Pattern Recognition — 11 citations into it
- Natural Language Processing — 7 citations into it
Whom Saeed Reza Aghabozorgi trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Eamonn J. Keogh
- T. Warren Liao
- Thorsten Joachims
- Philip Ka-Fai Chan
- Robert P. Schumaker
- Jessica Lin
- Raymond T. Ng
- Yuhan Cai
- Lei Chen
- Ella Bingham
Who trusts Saeed Reza Aghabozorgi overall
- Chunbin Lin
- Ali Seyed Shirkhorshidi
- B. Shravan Kumar
- Stefan Feuerriegel
- Romain Tavenard
- Kasun Bandara
- Laith Mohammad Abualigah
- Etienne Boursier
- Frank Xing
- Mika V. Mäntylä
Papers from Saeed Reza Aghabozorgi's perspective
Ordered by how strongly the researchers Saeed Reza Aghabozorgi trusts endorse each paper. Same corpus, a different order for every researcher.
- Discovering similar multidimensional trajectories (Proceedings / International Conference on Data Engineering)
- Text Categorization with Support Vector Machines: Learning with Many Relevant Features
- ImageNet classification with deep convolutional neural networks
- Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
- Fast Time Sequence Indexing for Arbitrary Lp Norms (Very Large Data Bases Conference)
- Some methods for classification and analysis of multivariate observations
- Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
- On the Need for Time Series Data Mining Benchmarks: A Survey and Empirical Demonstration
- LIBSVM: A library for support vector machines
- Gradient-based learning applied to document recognition
Their papers
- Text mining for market prediction: A systematic review (2014) — 621 citations
- Time-series clustering - A decade review (2015) — 1,740 citations
- Text mining of news-headlines for FOREX market prediction: A Multi-layer Dimension Reduction Algorithm with semantics and sentiment (2015) — 277 citations
- A Comparison Study on Similarity and Dissimilarity Measures in Clustering Continuous Data (2015) — 380 citations