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ORCIDMichal Lukasik
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2020 – today
- 2024
[j5]Michal Lukasik, Vaishnavh Nagarajan, Ankit Singh Rawat, Aditya Krishna Menon, Sanjiv Kumar:
What do larger image classifiers memorise? Trans. Mach. Learn. Res. 2024 (2024)- [c26]Michal Lukasik, Harikrishna Narasimhan, Aditya Krishna Menon, Felix Yu, Sanjiv Kumar:
Regression Aware Inference with LLMs. EMNLP (Findings) 2024: 13667-13678 - [c25]Lin Chen, Michal Lukasik, Wittawat Jitkrittum, Chong You, Sanjiv Kumar:
On Bias-Variance Alignment in Deep Models. ICLR 2024 - [c24]Yihan Wang, Si Si, Daliang Li, Michal Lukasik, Felix Yu, Cho-Jui Hsieh, Inderjit S. Dhillon, Sanjiv Kumar:
Two-stage LLM Fine-tuning with Less Specialization and More Generalization. ICLR 2024 - [i21]Michal Lukasik, Harikrishna Narasimhan, Aditya Krishna Menon, Felix X. Yu, Sanjiv Kumar:
Metric-aware LLM inference. CoRR abs/2403.04182 (2024) - 2023
- [c23]Daliang Li, Ankit Singh Rawat, Manzil Zaheer, Xin Wang, Michal Lukasik, Andreas Veit, Felix X. Yu, Sanjiv Kumar:
Large Language Models with Controllable Working Memory. ACL (Findings) 2023: 1774-1793 - [c22]Zitong Yang, Michal Lukasik, Vaishnavh Nagarajan, Zonglin Li, Ankit Singh Rawat, Manzil Zaheer, Aditya Krishna Menon, Sanjiv Kumar:
ResMem: Learn what you can and memorize the rest. NeurIPS 2023 - [c21]Serena Lutong Wang, Harikrishna Narasimhan, Yichen Zhou, Sara Hooker, Michal Lukasik, Aditya Krishna Menon:
Robust distillation for worst-class performance: on the interplay between teacher and student objectives. UAI 2023: 2237-2247 - [i20]Zitong Yang, Michal Lukasik, Vaishnavh Nagarajan, Zonglin Li, Ankit Singh Rawat, Manzil Zaheer, Aditya Krishna Menon, Sanjiv Kumar:
ResMem: Learn what you can and memorize the rest. CoRR abs/2302.01576 (2023) - [i19]Michal Lukasik, Vaishnavh Nagarajan, Ankit Singh Rawat, Aditya Krishna Menon, Sanjiv Kumar:
What do larger image classifiers memorise? CoRR abs/2310.05337 (2023) - [i18]Lin Chen, Michal Lukasik, Wittawat Jitkrittum, Chong You, Sanjiv Kumar:
It's an Alignment, Not a Trade-off: Revisiting Bias and Variance in Deep Models. CoRR abs/2310.09250 (2023) - 2022
- [j4]Michal Lukasik, Srinadh Bhojanapalli, Aditya Krishna Menon, Sanjiv Kumar:
Teacher's pet: understanding and mitigating biases in distillation. Trans. Mach. Learn. Res. 2022 (2022) - [c20]Rohan Tondulkar, Manisha Dubey, P. K. Srijith, Michal Lukasik:
Hawkes Process Classification through Discriminative Modeling of Text. IJCNN 2022: 1-8 - [i17]Serena Lutong Wang, Harikrishna Narasimhan, Yichen Zhou, Sara Hooker, Michal Lukasik, Aditya Krishna Menon:
Robust Distillation for Worst-class Performance. CoRR abs/2206.06479 (2022) - [i16]Wieslaw Kopec, Kinga Skorupska, Anna Jaskulska, Michal Lukasik, Barbara Karpowicz, Julia Paluch, Kinga Kwiatkowska, Daniel Jablonski, Rafal Maslyk:
XR Hackathon Going Online: Lessons Learned from a Case Study with Goethe-Institut. CoRR abs/2207.03833 (2022) - [i15]Yihan Wang, Si Si, Daliang Li, Michal Lukasik, Felix X. Yu, Cho-Jui Hsieh, Inderjit S. Dhillon, Sanjiv Kumar:
Preserving In-Context Learning ability in Large Language Model Fine-tuning. CoRR abs/2211.00635 (2022) - [i14]Daliang Li, Ankit Singh Rawat, Manzil Zaheer, Xin Wang, Michal Lukasik, Andreas Veit, Felix X. Yu, Sanjiv Kumar:
Large Language Models with Controllable Working Memory. CoRR abs/2211.05110 (2022) - 2021
- [c19]Wieslaw Kopec
, Kinga Skorupska, Anna Jaskulska, Michal Lukasik, Barbara Karpowicz, Julia Paluch, Kinga Kwiatkowska, Daniel Jablonski, Rafal Maslyk:
XR Hackathon Going Online: Lessons Learned from a Case Study with Goethe-Institute. MIDI 2021: 218-228 - [i13]Srinadh Bhojanapalli, Ayan Chakrabarti, Himanshu Jain, Sanjiv Kumar, Michal Lukasik, Andreas Veit:
Eigen Analysis of Self-Attention and its Reconstruction from Partial Computation. CoRR abs/2106.08823 (2021) - [i12]Michal Lukasik, Srinadh Bhojanapalli, Aditya Krishna Menon, Sanjiv Kumar:
Teacher's pet: understanding and mitigating biases in distillation. CoRR abs/2106.10494 (2021) - [i11]Srinadh Bhojanapalli, Ayan Chakrabarti, Andreas Veit, Michal Lukasik, Himanshu Jain, Frederick Liu, Yin-Wen Chang, Sanjiv Kumar:
Leveraging redundancy in attention with Reuse Transformers. CoRR abs/2110.06821 (2021) - [i10]Wittawat Jitkrittum, Michal Lukasik, Ananda Theertha Suresh, Felix X. Yu, Gang Wang:
HD-cos Networks: Efficient Neural Architectures for Secure Multi-Party Computation. CoRR abs/2110.15440 (2021) - 2020
- [c18]Michal Lukasik, Boris Dadachev, Kishore Papineni, Gonçalo Simões:
Text Segmentation by Cross Segment Attention. EMNLP (1) 2020: 4707-4716 - [c17]Michal Lukasik, Himanshu Jain, Aditya Krishna Menon, Seungyeon Kim, Srinadh Bhojanapalli, Felix X. Yu, Sanjiv Kumar:
Semantic Label Smoothing for Sequence to Sequence Problems. EMNLP (1) 2020: 4992-4998 - [c16]Michal Lukasik, Srinadh Bhojanapalli, Aditya Krishna Menon, Sanjiv Kumar:
Does label smoothing mitigate label noise? ICML 2020: 6448-6458 - [c15]Aleksandar Bojchevski, Johannes Klicpera, Bryan Perozzi, Amol Kapoor, Martin Blais, Benedek Rózemberczki, Michal Lukasik, Stephan Günnemann:
Scaling Graph Neural Networks with Approximate PageRank. KDD 2020: 2464-2473 - [i9]Michal Lukasik, Srinadh Bhojanapalli, Aditya Krishna Menon, Sanjiv Kumar:
Does label smoothing mitigate label noise? CoRR abs/2003.02819 (2020) - [i8]Michal Lukasik, Boris Dadachev, Gonçalo Simões, Kishore Papineni:
Text Segmentation by Cross Segment Attention. CoRR abs/2004.14535 (2020) - [i7]Aleksandar Bojchevski, Johannes Klicpera, Bryan Perozzi, Amol Kapoor, Martin Blais, Benedek Rózemberczki, Michal Lukasik, Stephan Günnemann:
Scaling Graph Neural Networks with Approximate PageRank. CoRR abs/2007.01570 (2020) - [i6]Michal Lukasik, Himanshu Jain, Aditya Krishna Menon, Seungyeon Kim, Srinadh Bhojanapalli, Felix X. Yu, Sanjiv Kumar:
Semantic Label Smoothing for Sequence to Sequence Problems. CoRR abs/2010.07447 (2020) - [i5]Rohan Tondulkar, Manisha Dubey, P. K. Srijith, Michal Lukasik:
Hawkes Process Classification through Discriminative Modeling of Text. CoRR abs/2010.11851 (2020)
2010 – 2019
- 2019
- [j3]Michal Lukasik, Kalina Bontcheva, Trevor Cohn, Arkaitz Zubiaga, Maria Liakata, Rob Procter:
Gaussian Processes for Rumour Stance Classification in Social Media. ACM Trans. Inf. Syst. 37(2): 20:1-20:24 (2019) - 2018
- [j2]Arkaitz Zubiaga, Elena Kochkina, Maria Liakata, Rob Procter, Michal Lukasik, Kalina Bontcheva, Trevor Cohn, Isabelle Augenstein:
Discourse-aware rumour stance classification in social media using sequential classifiers. Inf. Process. Manag. 54(2): 273-290 (2018) - [c14]Michal Lukasik, Richard Zens:
Content Explorer: Recommending Novel Entities for a Document Writer. EMNLP 2018: 3371-3380 - [c13]Sherin Thomas, P. K. Srijith, Michal Lukasik:
A Bayesian Point Process Model for User Return Time Prediction in Recommendation Systems. UMAP 2018: 363-364 - 2017
- [b1]Michal Lukasik:
Probabilistic modeling of rumour stance and popularity in social media. University of Sheffield, UK, 2017 - [c12]P. K. Srijith, Michal Lukasik, Kalina Bontcheva, Trevor Cohn:
Longitudinal Modeling of Social Media with Hawkes Process Based on Users and Networks. ASONAM 2017: 195-202 - [i4]Arkaitz Zubiaga, Elena Kochkina, Maria Liakata, Rob Procter, Michal Lukasik, Kalina Bontcheva, Trevor Cohn, Isabelle Augenstein:
Discourse-Aware Rumour Stance Classification in Social Media Using Sequential Classifiers. CoRR abs/1712.02223 (2017) - 2016
- [j1]Grzegorz Bokota, Marta Magnowska, Tomasz Kusmierczyk, Michal Lukasik, Matylda Roszkowska, Dariusz Plewczynski:
Computational Approach to Dendritic Spine Taxonomy and Shape Transition Analysis. Frontiers Comput. Neurosci. 10: 140 (2016) - [c11]Michal Lukasik, Trevor Cohn:
Convolution Kernels for Discriminative Learning from Streaming Text. AAAI 2016: 2757-2763 - [c10]Varvara Logacheva, Michal Lukasik, Lucia Specia:
Metrics for Evaluation of Word-level Machine Translation Quality Estimation. ACL (2) 2016 - [c9]Michal Lukasik, P. K. Srijith, Duy Vu, Kalina Bontcheva, Arkaitz Zubiaga, Trevor Cohn:
Hawkes Processes for Continuous Time Sequence Classification: an Application to Rumour Stance Classification in Twitter. ACL (2) 2016 - [c8]Arkaitz Zubiaga, Elena Kochkina, Maria Liakata, Rob Procter, Michal Lukasik:
Stance Classification in Rumours as a Sequential Task Exploiting the Tree Structure of Social Media Conversations. COLING 2016: 2438-2448 - [i3]Michal Lukasik, Kalina Bontcheva, Trevor Cohn, Arkaitz Zubiaga, Maria Liakata, Rob Procter:
Using Gaussian Processes for Rumour Stance Classification in Social Media. CoRR abs/1609.01962 (2016) - [i2]Arkaitz Zubiaga, Elena Kochkina, Maria Liakata, Rob Procter, Michal Lukasik:
Stance classification in Rumours as a Sequential Task Exploiting the Tree Structure of Social Media Conversations. CoRR abs/1609.09028 (2016) - 2015
- [c7]Michal Lukasik, Trevor Cohn, Kalina Bontcheva:
Point Process Modelling of Rumour Dynamics in Social Media. ACL (2) 2015: 518-523 - [c6]Michal Lukasik, P. K. Srijith, Trevor Cohn, Kalina Bontcheva:
Modeling Tweet Arrival Times using Log-Gaussian Cox Processes. EMNLP 2015: 250-255 - [c5]Michal Lukasik, Trevor Cohn, Kalina Bontcheva:
Classifying Tweet Level Judgements of Rumours in Social Media. EMNLP 2015: 2590-2595 - [i1]Michal Lukasik, Trevor Cohn, Kalina Bontcheva:
Estimating collective judgement of rumours in social media. CoRR abs/1506.00468 (2015) - 2013
- [c4]Dariusz Plewczynski, Michal Lukasik, Konrad Kurdej, Julian Zubek, Franciszek Rakowski, Joanna Raczaszek-Leonardi:
Generic Framework for Simulation of Cognitive Systems: A Case Study of Color Category Boundaries. ICMMI 2013: 385-393 - [c3]Indrajit Saha, Ujjwal Maulik, Michal Lukasik, Dariusz Plewczynski:
Multiobjective Differential Evolution: A Comparative Study on Benchmark Problems. ICMMI 2013: 529-536 - [c2]Michal Lukasik, Marcin Sydow:
Threshold ML-KNN: Statistical Evaluation on Multiple Benchmarks. IIS 2013: 198-205 - [p2]Michal Lukasik, Tomasz Kusmierczyk, Lukasz Bolikowski, Hung Son Nguyen:
Hierarchical, Multi-label Classification of Scholarly Publications: Modifications of ML-KNN Algorithm. Intelligent Tools for Building a Scientific Information Platform 2013: 343-363 - [p1]Tomasz Kusmierczyk, Michal Lukasik, Lukasz Bolikowski, Hung Son Nguyen:
Comparing Hierarchical Mathematical Document Clustering against the Mathematics Subject Classification Tree. Intelligent Tools for Building a Scientific Information Platform 2013: 365-392 - 2012
- [c1]Piotr Jan Dendek, Lukasz Bolikowski, Michal Lukasik:
Evaluation of Features for Author Name Disambiguation Using Linear Support Vector Machines. Document Analysis Systems 2012: 440-444
Coauthor Index
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last updated on 2024-11-19 21:48 CET by the dblp team
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