Andrey Gritsenko

21 papers A* 2B 2Misc 1Journal 10Unranked 6

Year	Rank	Type	Title / Venue / Authors
2023	J	`jnl`	Graph transfer learning. Knowl. Inf. Syst. Andrey Gritsenko, Kimia Shayestehfard, Yuan Guo, Armin Moharrer, Jennifer G. Dy, Stratis Ioannidis
2021	A*	`conf`	Graph Transfer Learning. ICDM Andrey Gritsenko, Yuan Guo, Kimia Shayestehfard, Armin Moharrer, Jennifer G. Dy, Stratis Ioannidis
2020	J	`jnl`	Deep Learning for RF Fingerprinting: A Massive Experimental Study. IEEE Internet Things Mag. Tong Jian, Bruno Costa Rendon, Emmanuel Ojuba, Nasim Soltani, Zifeng Wang, Kunal Sankhe, Andrey Gritsenko, Jennifer G. Dy, Kaushik R. Chowdhury, Stratis Ioannidis
2020	J	`jnl`	Embedded spectral descriptors: learning the point-wise correspondence metric via Siamese neural networks. J. Comput. Des. Eng. Zhiyu Sun, Yusen He, Andrey Gritsenko, Amaury Lendasse, Stephen Baek
2020	A*	`conf`	Open-World Class Discovery with Kernel Networks. ICDM Zifeng Wang, Batool Salehi, Andrey Gritsenko, Kaushik R. Chowdhury, Stratis Ioannidis, Jennifer G. Dy
2020	J	`jnl`	Open-World Class Discovery with Kernel Networks. CoRR Zifeng Wang, Batool Salehi, Andrey Gritsenko, Kaushik R. Chowdhury, Stratis Ioannidis, Jennifer G. Dy
2020	—	`conf`	Twin Classification in Resting-State Brain Connectivity. ISBI Andrey Gritsenko, Martin A. Lindquist, Moo K. Chung
2019	—	`conf`	Circular Pearson Correlation Using Cosine Series Expansion. ISBI Shih-Gu Huang, Andrey Gritsenko, Martin A. Lindquist, Moo K. Chung
2019	—	`conf`	Finding a 'New' Needle in the Haystack: Unseen Radio Detection in Large Populations Using Deep Learning. DySPAN Andrey Gritsenko, Zifeng Wang, Tong Jian, Jennifer G. Dy, Kaushik R. Chowdhury, Stratis Ioannidis
2019	J	`jnl`	Incremental ELMVIS for unsupervised learning. CoRR Anton Akusok, Emil Eirola, Yoan Miche, Ian Oliver, Kaj-Mikael Björk, Andrey Gritsenko, Stephen Baek, Amaury Lendasse
2019	—	`conf`	MAC ID Spoofing-Resistant Radio Fingerprinting. GlobalSIP Tong Jian, Bruno Costa Rendon, Andrey Gritsenko, Jennifer G. Dy, Kaushik R. Chowdhury, Stratis Ioannidis
2019	—	`conf`	Statistical Inference on the Number of Cycles in Brain Networks. ISBI Moo K. Chung, Shih-Gu Huang, Andrey Gritsenko, Li Shen, Hyekyoung Lee
2018	J	`jnl`	Extreme Learning Machines for VISualization+R: Mastering Visualization with Target Variables. Cogn. Comput. Andrey Gritsenko, Anton Akusok, Stephen Baek, Yoan Miche, Amaury Lendasse
2018	J	`jnl`	Hill Climbing Optimized Twin Classification Using Resting-State Functional MRI. CoRR Andrey Gritsenko, Martin A. Lindquist, Gregory R. Kirk, Moo K. Chung
2017	J	`jnl`	Adding reliability to ELM forecasts by confidence intervals. Neurocomputing Anton Akusok, Andrey Gritsenko, Yoan Miche, Kaj-Mikael Björk, Rui Nian, Paula Lauren, Amaury Lendasse
2017	B	`conf`	Advanced query strategies for Active Learning with Extreme Learning Machines. ESANN Anton Akusok, Emil Eirola, Yoan Miché, Andrey Gritsenko, Amaury Lendasse
2017	J	`jnl`	Deep Spectral Descriptors: Learning the point-wise correspondence metric via Siamese deep neural networks. CoRR Zhiyu Sun, Yusen He, Andrey Gritsenko, Amaury Lendasse, Stephen Baek
2017	Misc	`conf`	Solve Classification Tasks with Probabilities. Statistically-Modeled Outputs. HAIS Andrey Gritsenko, Emil Eirola, Daniel Schupp, Edward R. Ratner, Amaury Lendasse
2016	B	`conf`	Combined nonlinear visualization and classification: ELMVIS++C. IJCNN Andrey Gritsenko, Anton Akusok, Yoan Miché, Kaj-Mikael Björk, Stephen Baek, Amaury Lendasse
2015	—	`conf`	Extreme Learning Machines for Multiclass Classification: Refining Predictions with Gaussian Mixture Models. IWANN (2) Emil Eirola, Andrey Gritsenko, Anton Akusok, Kaj-Mikael Björk, Yoan Miche, Dusan Sovilj, Rui Nian, Bo He, Amaury Lendasse
2013	J	`jnl`	A Workflow-Forecast Approach To The Task Scheduling Problem In Distributed Computing Systems. CoRR Andrey Gritsenko