Mykola Pechenizkiy

ORCID

Publication Activity (10 Years)

Years Active: 2002-2024
Publications (10 Years): 227

Top Venues

CoRR

EDM

NeurIPS

Data Min. Knowl. Discov.

Publications

Hilde J. P. Weerts, Florian Pfisterer, Matthias Feurer, Katharina Eggensperger, Edward Bergman, Noor H. Awad, Joaquin Vanschoren, Mykola Pechenizkiy, Bernd Bischl, Frank Hutter
Can Fairness be Automated? Guidelines and Opportunities for Fairness-aware AutoML. J. Artif. Intell. Res. 79 (2024)
Meng Fang, Shilong Deng, Yudi Zhang, Zijing Shi, Ling Chen, Mykola Pechenizkiy, Jun Wang
Large Language Models Are Neurosymbolic Reasoners. CoRR (2024)
Hilde J. P. Weerts, Florian Pfisterer, Matthias Feurer, Katharina Eggensperger, Edward Bergman, Noor H. Awad, Joaquin Vanschoren, Mykola Pechenizkiy, Bernd Bischl, Frank Hutter
Can Fairness be Automated? Guidelines and Opportunities for Fairness-aware AutoML. CoRR (2023)
Lu Yin, Gen Li, Meng Fang, Li Shen, Tianjin Huang, Zhangyang Wang, Vlado Menkovski, Xiaolong Ma, Mykola Pechenizkiy, Shiwei Liu
Dynamic Sparsity Is Channel-Level Sparsity Learner. NeurIPS (2023)
Tianjin Huang, Shiwei Liu, Tianlong Chen, Meng Fang, Li Shen, Vlado Menkovski, Lu Yin, Yulong Pei, Mykola Pechenizkiy
Enhancing Adversarial Training via Reweighting Optimization Trajectory. ECML/PKDD (1) (2023)
Hilde J. P. Weerts, Raphaële Xenidis, Fabien Tarissan, Henrik Palmer Olsen, Mykola Pechenizkiy
Algorithmic Unfairness through the Lens of EU Non-Discrimination Law: Or Why the Law is not a Decision Tree. FAccT (2023)
Ricky Maulana Fajri, Yulong Pei, Lu Yin, Mykola Pechenizkiy
A Structural-Clustering Based Active Learning for Graph Neural Networks. CoRR (2023)
Shiwei Liu, Tianlong Chen, Xiaohan Chen, Xuxi Chen, Qiao Xiao, Boqian Wu, Tommi Kärkkäinen, Mykola Pechenizkiy, Decebal Constantin Mocanu, Zhangyang Wang
More ConvNets in the 2020s: Scaling up Kernels Beyond 51x51 using Sparsity. ICLR (2023)
Akrati Saxena, Cristina Gutiérrez Bierbooms, Mykola Pechenizkiy
Fairness-aware fake news mitigation using counter information propagation. Appl. Intell. 53 (22) (2023)
Hilde J. P. Weerts, Raphaël Xenidis, Fabien Tarissan, Henrik Palmer Olsen, Mykola Pechenizkiy
Algorithmic Unfairness through the Lens of EU Non-Discrimination Law: Or Why the Law is not a Decision Tree. CoRR (2023)
Dennis Collaris, Pratik Gajane, Joost Jorritsma, Jarke J. van Wijk, Mykola Pechenizkiy
LEMON: Alternative Sampling for More Faithful Explanation Through Local Surrogate Models. IDA (2023)
Iftitahu Ni'mah, Meng Fang, Vlado Menkovski, Mykola Pechenizkiy
NLG Evaluation Metrics Beyond Correlation Analysis: An Empirical Metric Preference Checklist. ACL (1) (2023)
Lu Yin, Gen Li, Meng Fang, Li Shen, Tianjin Huang, Zhangyang Wang, Vlado Menkovski, Xiaolong Ma, Mykola Pechenizkiy, Shiwei Liu
Dynamic Sparsity Is Channel-Level Sparsity Learner. CoRR (2023)
Lu Yin, Shiwei Liu, Meng Fang, Tianjin Huang, Vlado Menkovski, Mykola Pechenizkiy
Lottery Pools: Winning More by Interpolating Tickets without Increasing Training or Inference Cost. AAAI (2023)
Hilde J. P. Weerts, Raphaële Xenidis, Fabien Tarissan, Henrik Palmer Olsen, Mykola Pechenizkiy
Algorithmic Unfairness Through the Lens of EU Non-Discrimination Law. EWAF (2023)
Zahra Atashgahi, Mykola Pechenizkiy, Raymond N. J. Veldhuis, Decebal Constantin Mocanu
Adaptive Sparsity Level during Training for Efficient Time Series Forecasting with Transformers. CoRR (2023)
Yudi Zhang, Yali Du, Biwei Huang, Ziyan Wang, Jun Wang, Meng Fang, Mykola Pechenizkiy
Interpretable Reward Redistribution in Reinforcement Learning: A Causal Approach. NeurIPS (2023)
Tianjin Huang, Shiwei Liu, Tianlong Chen, Meng Fang, Li Shen, Vlado Menkovski, Lu Yin, Yulong Pei, Mykola Pechenizkiy
Enhancing Adversarial Training via Reweighting Optimization Trajectory. CoRR (2023)
Yudi Zhang, Yali Du, Biwei Huang, Ziyan Wang, Jun Wang, Meng Fang, Mykola Pechenizkiy
GRD: A Generative Approach for Interpretable Reward Redistribution in Reinforcement Learning. CoRR (2023)
Jiaxu Zhao, Meng Fang, Zijing Shi, Yitong Li, Ling Chen, Mykola Pechenizkiy
CHBias: Bias Evaluation and Mitigation of Chinese Conversational Language Models. ACL (1) (2023)
Zahra Atashgahi, Xuhao Zhang, Neil Kichler, Shiwei Liu, Lu Yin, Mykola Pechenizkiy, Raymond N. J. Veldhuis, Decebal Constantin Mocanu
Supervised Feature Selection with Neuron Evolution in Sparse Neural Networks. CoRR (2023)
Jiaxu Zhao, Meng Fang, Shirui Pan, Wenpeng Yin, Mykola Pechenizkiy
GPTBIAS: A Comprehensive Framework for Evaluating Bias in Large Language Models. CoRR (2023)
Syed Ihtesham Hussain Shah, Muddasar Naeem, Giovanni Paragliola, Antonio Coronato, Mykola Pechenizkiy
An AI-empowered infrastructure for risk prevention during medical examination. Expert Syst. Appl. 225 (2023)
Bram Grooten, Ghada Sokar, Shibhansh Dohare, Elena Mocanu, Matthew E. Taylor, Mykola Pechenizkiy, Decebal Constantin Mocanu
Automatic Noise Filtering with Dynamic Sparse Training in Deep Reinforcement Learning. CoRR (2023)
Zahra Atashgahi, Xuhao Zhang, Neil Kichler, Shiwei Liu, Lu Yin, Mykola Pechenizkiy, Raymond N. J. Veldhuis, Decebal Constantin Mocanu
Supervised Feature Selection with Neuron Evolution in Sparse Neural Networks. Trans. Mach. Learn. Res. 2023 (2023)
Lu Yin, You Wu, Zhenyu Zhang, Cheng-Yu Hsieh, Yaqing Wang, Yiling Jia, Mykola Pechenizkiy, Yi Liang, Zhangyang Wang, Shiwei Liu
Outlier Weighed Layerwise Sparsity (OWL): A Missing Secret Sauce for Pruning LLMs to High Sparsity. CoRR (2023)
Bram Grooten, Ghada Sokar, Shibhansh Dohare, Elena Mocanu, Matthew E. Taylor, Mykola Pechenizkiy, Decebal Constantin Mocanu
Automatic Noise Filtering with Dynamic Sparse Training in Deep Reinforcement Learning. AAMAS (2023)
Tristan Tomilin, Meng Fang, Yudi Zhang, Mykola Pechenizkiy
COOM: A Game Benchmark for Continual Reinforcement Learning. NeurIPS (2023)
Tianjin Huang, Lu Yin, Zhenyu Zhang, Li Shen, Meng Fang, Mykola Pechenizkiy, Zhangyang Wang, Shiwei Liu
Are Large Kernels Better Teachers than Transformers for ConvNets? ICML (2023)
Ben Halstead, Yun Sing Koh, Patricia Riddle, Mykola Pechenizkiy, Albert Bifet
Combining Diverse Meta-Features to Accurately Identify Recurring Concept Drift in Data Streams. ACM Trans. Knowl. Discov. Data 17 (8) (2023)
Bram Grooten, Tristan Tomilin, Gautham Vasan, Matthew E. Taylor, A. Rupam Mahmood, Meng Fang, Mykola Pechenizkiy, Decebal Constantin Mocanu
MaDi: Learning to Mask Distractions for Generalization in Visual Deep Reinforcement Learning. CoRR (2023)
Danil Provodin, Pratik Gajane, Mykola Pechenizkiy, Maurits Kaptein
Provably Efficient Exploration in Constrained Reinforcement Learning: Posterior Sampling Is All You Need. CoRR (2023)
Sheetal Borar, Hilde J. P. Weerts, Binyam Gebre, Mykola Pechenizkiy
Improving Recommender System Diversity with Variational Autoencoders. BIAS (2023)
Zirui Liang, Yuntao Li, Tianjin Huang, Akrati Saxena, Yulong Pei, Mykola Pechenizkiy
Heterophily-Based Graph Neural Network for Imbalanced Classification. CoRR (2023)
Iftitahu Ni'mah, Samaneh Khoshrou, Vlado Menkovski, Mykola Pechenizkiy
KeyGen2Vec: Learning Document Embedding via Multi-label Keyword Generation in Question-Answering. CoRR (2023)
Tianjin Huang, Lu Yin, Zhenyu Zhang, Li Shen, Meng Fang, Mykola Pechenizkiy, Zhangyang Wang, Shiwei Liu
Are Large Kernels Better Teachers than Transformers for ConvNets? CoRR (2023)
Ben Halstead, Yun Sing Koh, Patricia Riddle, Mykola Pechenizkiy, Albert Bifet
FALL: A Modular Adaptive Learning Platform for Streaming Data. ICDE (2023)
Boqian Wu, Qiao Xiao, Shiwei Liu, Lu Yin, Mykola Pechenizkiy, Decebal Constantin Mocanu, Maurice van Keulen, Elena Mocanu
E2ENet: Dynamic Sparse Feature Fusion for Accurate and Efficient 3D Medical Image Segmentation. CoRR (2023)
Jiaxu Zhao, Lu Yin, Shiwei Liu, Meng Fang, Mykola Pechenizkiy
REST: Enhancing Group Robustness in DNNs through Reweighted Sparse Training. CoRR (2023)
Can Jin, Tianjin Huang, Yihua Zhang, Mykola Pechenizkiy, Sijia Liu, Shiwei Liu, Tianlong Chen
Visual Prompting Upgrades Neural Network Sparsification: A Data-Model Perspective. CoRR (2023)
Jiaxu Zhao, Lu Yin, Shiwei Liu, Meng Fang, Mykola Pechenizkiy
REST: Enhancing Group Robustness in DNNs Through Reweighted Sparse Training. ECML/PKDD (2) (2023)
Iftitahu Ni'mah, Meng Fang, Vlado Menkovski, Mykola Pechenizkiy
NLG Evaluation Metrics Beyond Correlation Analysis: An Empirical Metric Preference Checklist. CoRR (2023)
Jiaxu Zhao, Meng Fang, Zijing Shi, Yitong Li, Ling Chen, Mykola Pechenizkiy
CHBias: Bias Evaluation and Mitigation of Chinese Conversational Language Models. CoRR (2023)
Shiwei Liu, Tianlong Chen, Xiaohan Chen, Li Shen, Decebal Constantin Mocanu, Zhangyang Wang, Mykola Pechenizkiy
The Unreasonable Effectiveness of Random Pruning: Return of the Most Naive Baseline for Sparse Training. CoRR (2022)
Lu Yin, Shiwei Liu, Meng Fang, Tianjin Huang, Vlado Menkovski, Mykola Pechenizkiy
Lottery Pools: Winning More by Interpolating Tickets without Increasing Training or Inference Cost. CoRR (2022)
Jefrey Lijffijt, Dimitra Gkorou, Pieter Van Hertum, Alexander Ypma, Mykola Pechenizkiy, Joaquin Vanschoren
Introduction to the Special Section on AI in Manufacturing: Current Trends and Challenges. SIGKDD Explor. 24 (2) (2022)
Yulong Pei, Tianjin Huang, Werner van Ipenburg, Mykola Pechenizkiy
ResGCN: attention-based deep residual modeling for anomaly detection on attributed networks. Mach. Learn. 111 (2) (2022)
Akrati Saxena, George Fletcher, Mykola Pechenizkiy
FairSNA: Algorithmic Fairness in Social Network Analysis. CoRR (2022)
Danil Provodin, Pratik Gajane, Mykola Pechenizkiy, Maurits Kaptein
An Empirical Evaluation of Posterior Sampling for Constrained Reinforcement Learning. CoRR (2022)
Zahra Atashgahi, Ghada Sokar, Tim van der Lee, Elena Mocanu, Decebal Constantin Mocanu, Raymond N. J. Veldhuis, Mykola Pechenizkiy
Quick and robust feature selection: the strength of energy-efficient sparse training for autoencoders. Mach. Learn. 111 (1) (2022)
Masoud Mansoury, Himan Abdollahpouri, Mykola Pechenizkiy, Bamshad Mobasher, Robin Burke
A Graph-Based Approach for Mitigating Multi-Sided Exposure Bias in Recommender Systems. ACM Trans. Inf. Syst. 40 (2) (2022)
Rianne Margaretha Schouten, Wouter Duivesteijn, Mykola Pechenizkiy
Exceptional Model Mining for Repeated Cross-Sectional Data (EMM-RCS). SDM (2022)
Afrizal Doewes, Akrati Saxena, Yulong Pei, Mykola Pechenizkiy
Individual Fairness Evaluation for Automated Essay Scoring System. EDM (2022)
Tianjin Huang, Vlado Menkovski, Yulong Pei, Yuhao Wang, Mykola Pechenizkiy
Direction-aggregated Attack for Transferable Adversarial Examples. ACM J. Emerg. Technol. Comput. Syst. 18 (3) (2022)
Shiwei Liu, Tianlong Chen, Zahra Atashgahi, Xiaohan Chen, Ghada Sokar, Elena Mocanu, Mykola Pechenizkiy, Zhangyang Wang, Decebal Constantin Mocanu
Deep Ensembling with No Overhead for either Training or Testing: The All-Round Blessings of Dynamic Sparsity. ICLR (2022)
Danil Provodin, Pratik Gajane, Mykola Pechenizkiy, Maurits Kaptein
The Impact of Batch Learning in Stochastic Linear Bandits. CoRR (2022)
Shiwei Liu, Tianlong Chen, Xiaohan Chen, Li Shen, Decebal Constantin Mocanu, Zhangyang Wang, Mykola Pechenizkiy
The Unreasonable Effectiveness of Random Pruning: Return of the Most Naive Baseline for Sparse Training. ICLR (2022)
Akrati Saxena, George Fletcher, Mykola Pechenizkiy
NodeSim: node similarity based network embedding for diverse link prediction. EPJ Data Sci. 11 (1) (2022)
Qiao Xiao, Boqian Wu, Yu Zhang, Shiwei Liu, Mykola Pechenizkiy, Elena Mocanu, Decebal Constantin Mocanu
Dynamic Sparse Network for Time Series Classification: Learning What to "See". NeurIPS (2022)
Zahra Atashgahi, Decebal Constantin Mocanu, Raymond N. J. Veldhuis, Mykola Pechenizkiy
Memory-free Online Change-point Detection: A Novel Neural Network Approach. CoRR (2022)
Hilde J. P. Weerts, Lambèr Royakkers, Mykola Pechenizkiy
Does the End Justify the Means? On the Moral Justification of Fairness-Aware Machine Learning. CoRR (2022)
Dennis Collaris, Hilde J. P. Weerts, Daphne Miedema, Jarke J. van Wijk, Mykola Pechenizkiy
Characterizing Data Scientists' Mental Models of Local Feature Importance. NordiCHI (2022)
Lu Yin, Vlado Menkovski, Yulong Pei, Mykola Pechenizkiy
Semantic-Based Few-Shot Classification by Psychometric Learning. IDA (2022)
Ben Halstead, Yun Sing Koh, Patricia Riddle, Russel Pears, Mykola Pechenizkiy, Albert Bifet, Gustavo Olivares, Guy Coulson
Analyzing and repairing concept drift adaptation in data stream classification. Mach. Learn. 111 (10) (2022)
Ghada Sokar, Zahra Atashgahi, Mykola Pechenizkiy, Decebal Constantin Mocanu
Where to Pay Attention in Sparse Training for Feature Selection? NeurIPS (2022)
Ben Halstead, Yun Sing Koh, Patricia Riddle, Mykola Pechenizkiy, Albert Bifet
A Probabilistic Framework for Adapting to Changing and Recurring Concepts in Data Streams. DSAA (2022)
Ghada Sokar, Zahra Atashgahi, Mykola Pechenizkiy, Decebal Constantin Mocanu
Where to Pay Attention in Sparse Training for Feature Selection? CoRR (2022)
Tianjin Huang, Yulong Pei, Vlado Menkovski, Mykola Pechenizkiy
Hop-Count Based Self-supervised Anomaly Detection on Attributed Networks. ECML/PKDD (1) (2022)
Lu Yin, Vlado Menkovski, Meng Fang, Tianjin Huang, Yulong Pei, Mykola Pechenizkiy
Superposing many tickets into one: A performance booster for sparse neural network training. UAI (2022)
Tristan Tomilin, Tianhong Dai, Meng Fang, Mykola Pechenizkiy
LevDoom: A Benchmark for Generalization on Level Difficulty in Reinforcement Learning. CoG (2022)
Danil Provodin, Pratik Gajane, Mykola Pechenizkiy, Maurits Kaptein
The Impact of Batch Learning in Stochastic Linear Bandits. ICDM (2022)
Ricky Maulana Fajri, Akrati Saxena, Yulong Pei, Mykola Pechenizkiy
FAL-CUR: Fair Active Learning using Uncertainty and Representativeness on Fair Clustering. CoRR (2022)
Qiao Xiao, Boqian Wu, Yu Zhang, Shiwei Liu, Mykola Pechenizkiy, Elena Mocanu, Decebal Constantin Mocanu
Dynamic Sparse Network for Time Series Classification: Learning What to "see". CoRR (2022)
Ghada Sokar, Elena Mocanu, Decebal Constantin Mocanu, Mykola Pechenizkiy, Peter Stone
Dynamic Sparse Training for Deep Reinforcement Learning. IJCAI (2022)
Fang Lv, Wei Wang, Linxuan Han, Di Wang, Yulong Pei, Junheng Huang, Bailing Wang, Mykola Pechenizkiy
Mining trading patterns of pyramid schemes from financial time series data. Future Gener. Comput. Syst. 134 (2022)
Zahra Atashgahi, Joost Pieterse, Shiwei Liu, Decebal Constantin Mocanu, Raymond N. J. Veldhuis, Mykola Pechenizkiy
A brain-inspired algorithm for training highly sparse neural networks. Mach. Learn. 111 (12) (2022)
Akrati Saxena, George Fletcher, Mykola Pechenizkiy
HM-EIICT: Fairness-aware link prediction in complex networks using community information. J. Comb. Optim. 44 (4) (2022)
Shiwei Liu, Tianlong Chen, Xiaohan Chen, Xuxi Chen, Qiao Xiao, Boqian Wu, Mykola Pechenizkiy, Decebal Constantin Mocanu, Zhangyang Wang
More ConvNets in the 2020s: Scaling up Kernels Beyond 51x51 using Sparsity. CoRR (2022)
Yibin Lei, Yu Cao, Dianqi Li, Tianyi Zhou, Meng Fang, Mykola Pechenizkiy
Phrase-level Textual Adversarial Attack with Label Preservation. CoRR (2022)
Rianne M. Schouten, Marcos L. P. Bueno, Wouter Duivesteijn, Mykola Pechenizkiy
Mining sequences with exceptional transition behaviour of varying order using quality measures based on information-theoretic scoring functions. Data Min. Knowl. Discov. 36 (1) (2022)
Yibin Lei, Yu Cao, Dianqi Li, Tianyi Zhou, Meng Fang, Mykola Pechenizkiy
Phrase-level Textual Adversarial Attack with Label Preservation. NAACL-HLT (Findings) (2022)
Ghada Sokar, Decebal Constantin Mocanu, Mykola Pechenizkiy
Avoiding Forgetting and Allowing Forward Transfer in Continual Learning via Sparse Networks. ECML/PKDD (3) (2022)
Collin F. Lynch, Mirko Marras, Mykola Pechenizkiy, Anna N. Rafferty, Steven Ritter, Vinitra Swamy, Renzhe Yu
FATED 2022: Fairness, Accountability, and Transparency in Educational Data. EDM (2022)
Pratik Gajane, Akrati Saxena, Maryam Tavakol, George Fletcher, Mykola Pechenizkiy
Survey on Fair Reinforcement Learning: Theory and Practice. CoRR (2022)
Lu Yin, Vlado Menkovski, Meng Fang, Tianjin Huang, Yulong Pei, Mykola Pechenizkiy, Decebal Constantin Mocanu, Shiwei Liu
Superposing Many Tickets into One: A Performance Booster for Sparse Neural Network Training. CoRR (2022)
Tianjin Huang, Tianlong Chen, Meng Fang, Vlado Menkovski, Jiaxu Zhao, Lu Yin, Yulong Pei, Decebal Constantin Mocanu, Zhangyang Wang, Mykola Pechenizkiy, Shiwei Liu
You Can Have Better Graph Neural Networks by Not Training Weights at All: Finding Untrained GNNs Tickets. LoG (2022)
Tianjin Huang, Tianlong Chen, Meng Fang, Vlado Menkovski, Jiaxu Zhao, Lu Yin, Yulong Pei, Decebal Constantin Mocanu, Zhangyang Wang, Mykola Pechenizkiy, Shiwei Liu
You Can Have Better Graph Neural Networks by Not Training Weights at All: Finding Untrained GNNs Tickets. CoRR (2022)
Shiwei Liu, Decebal Constantin Mocanu, Amarsagar Reddy Ramapuram Matavalam, Yulong Pei, Mykola Pechenizkiy
Sparse evolutionary deep learning with over one million artificial neurons on commodity hardware. Neural Comput. Appl. 33 (7) (2021)
Shiwei Liu, Tianlong Chen, Zahra Atashgahi, Xiaohan Chen, Ghada Sokar, Elena Mocanu, Mykola Pechenizkiy, Zhangyang Wang, Decebal Constantin Mocanu
FreeTickets: Accurate, Robust and Efficient Deep Ensemble by Training with Dynamic Sparsity. CoRR (2021)
Ghada Sokar, Decebal Constantin Mocanu, Mykola Pechenizkiy
Self-Attention Meta-Learner for Continual Learning. AAMAS (2021)
Danil Provodin, Pratik Gajane, Mykola Pechenizkiy, Maurits Kaptein
The Impact of Batch Learning in Stochastic Bandits. CoRR (2021)
Lu Yin, Vlado Menkovski, Shiwei Liu, Mykola Pechenizkiy
Hierarchical Semantic Segmentation using Psychometric Learning. ACML (2021)
Lu Yin, Vlado Menkovski, Shiwei Liu, Mykola Pechenizkiy
Hierarchical Semantic Segmentation using Psychometric Learning. CoRR (2021)
Ben Halstead, Yun Sing Koh, Patricia Riddle, Mykola Pechenizkiy, Albert Bifet, Russel Pears
Fingerprinting Concepts in Data Streams with Supervised and Unsupervised Meta-Information. ICDE (2021)
Ghada Sokar, Decebal Constantin Mocanu, Mykola Pechenizkiy
Addressing the Stability-Plasticity Dilemma via Knowledge-Aware Continual Learning. CoRR (2021)
Lu Yin, Vlado Menkovski, Yulong Pei, Mykola Pechenizkiy
Semantic-Based Few-Shot Learning by Interactive Psychometric Testing. CoRR (2021)
Afrizal Doewes, Mykola Pechenizkiy
On the Limitations of Human-Computer Agreement in Automated Essay Scoring. EDM (2021)
Shiwei Liu, Lu Yin, Decebal Constantin Mocanu, Mykola Pechenizkiy
Do We Actually Need Dense Over-Parameterization? In-Time Over-Parameterization in Sparse Training. CoRR (2021)
Shiwei Liu, Tianlong Chen, Xiaohan Chen, Zahra Atashgahi, Lu Yin, Huanyu Kou, Li Shen, Mykola Pechenizkiy, Zhangyang Wang, Decebal Constantin Mocanu
Sparse Training via Boosting Pruning Plasticity with Neuroregeneration. NeurIPS (2021)
Ghada Sokar, Decebal Constantin Mocanu, Mykola Pechenizkiy
Self-Attention Meta-Learner for Continual Learning. CoRR (2021)

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Publication Activity (10 Years)

Top Topics

Top Venues

Mykola Pechenizkiy