An Algorithm for Finding Invariant Algebraic Curves of a Given Degree for Polynomial Planar Vector Fields. - Grzegorz Swirszcz (Int. J. Bifurc. Chaos, 2005)

Maximum weight independent sets and matchings in sparse random graphs. Exact results using the local weak convergence method. - David Gamarnik; Tomasz Nowicki; Grzegorz Swirszcz (Random Struct. Algorithms, 2006)

l1 Regularization in Infinite Dimensional Feature Spaces. - Saharon Rosset; Grzegorz Swirszcz; Nathan Srebro; Ji Zhu (COLT, 2007)

Inventory allocation and transportation scheduling for logistics of network-centric military operations. - Francisco Barahona; Pawan Chowdhary; Markus Ettl; Pu Huang; Tracy Kimbrel; Laszlo Ladányi; Young M. Lee; Baruch Schieber; Karthik Sourirajan; Maxim Sviridenko; Grzegorz Swirszcz (IBM J. Res. Dev., 2007)

Breast cancer identification: KDD CUP winner's report. - Claudia Perlich; Prem Melville; Yan Liu 002; Grzegorz Swirszcz; Richard D. Lawrence; Saharon Rosset (SIGKDD Explor., 2008)

Grouped Orthogonal Matching Pursuit for Variable Selection and Prediction. - Aurélie C. Lozano; Grzegorz Swirszcz; Naoki Abe (NIPS, 2009)

Winning the KDD Cup Orange Challenge with Ensemble Selection. - Alexandru Niculescu-Mizil; Claudia Perlich; Grzegorz Swirszcz; Vikas Sindhwani; Yan Liu 002; Prem Melville; Dong Wang; Jing Xiao; Jianying Hu; Moninder Singh; Wei Xiong Shang; Yanfeng Zhu 001 (KDD Cup, 2009)

Ensemble-Based Method for Task 2: Predicting Traffic Jam. - Jingrui He; Qing He; Grzegorz Swirszcz; Yiannis Kamarianakis; Rick Lawrence; Wei Shen; Laura Wynter (ICDM Workshops, 2010)

Traffic Velocity Prediction Using GPS Data: IEEE ICDM Contest Task 3 Report. - Wei Shen; Yiannis Kamarianakis; Laura Wynter; Jingrui He; Qing He; Rick Lawrence; Grzegorz Swirszcz (ICDM Workshops, 2010)

Medical data mining: insights from winning two competitions. - Saharon Rosset; Claudia Perlich; Grzegorz Swirszcz; Prem Melville; Yan Liu 002 (Data Min. Knowl. Discov., 2010)

On cross-validation and stacking: building seemingly predictive models on random data. - Claudia Perlich; Grzegorz Swirszcz (SIGKDD Explor., 2010)

Group Orthogonal Matching Pursuit for Logistic Regression. - Aurélie C. Lozano; Grzegorz Swirszcz; Naoki Abe (AISTATS, 2011)

Multi-level Lasso for Sparse Multi-task Regression. - Aurélie C. Lozano; Grzegorz Swirszcz (ICML, 2012)

Lattice-free sets, multi-branch split disjunctions, and mixed-integer programming. - Sanjeeb Dash; Neil B. Dobbs; Oktay Günlük; Tomasz Nowicki; Grzegorz Swirszcz (Math. Program., 2014)

Distance Geometry on the Sphere. - Leo Liberti; Grzegorz Swirszcz; Carlile Lavor (JCDCGG, 2015)

Approximation algorithms for the joint replenishment problem with deadlines. - Marcin Bienkowski; Jaroslaw Byrka; Marek Chrobak; Neil B. Dobbs; Tomasz Nowicki; Maxim Sviridenko; Grzegorz Swirszcz; Neal E. Young (J. Sched., 2015)

Local minima in training of deep networks. - Grzegorz Swirszcz; Wojciech Marian Czarnecki; Razvan Pascanu (CoRR, 2016)

Understanding Synthetic Gradients and Decoupled Neural Interfaces. - Wojciech Marian Czarnecki; Grzegorz Swirszcz; Max Jaderberg; Simon Osindero; Oriol Vinyals; Koray Kavukcuoglu (ICML, 2017)

Sobolev Training for Neural Networks. - Wojciech M. Czarnecki; Simon Osindero; Max Jaderberg; Grzegorz Swirszcz; Razvan Pascanu (NIPS, 2017)

Strength in Numbers: Trading-off Robustness and Computation via Adversarially-Trained Ensembles. - Edward Grefenstette; Robert Stanforth; Brendan O'Donoghue; Jonathan Uesato; Grzegorz Swirszcz; Pushmeet Kohli (CoRR, 2018)

Distilling Policy Distillation. - Wojciech M. Czarnecki; Razvan Pascanu; Simon Osindero; Siddhant M. Jayakumar; Grzegorz Swirszcz; Max Jaderberg (AISTATS, 2019)

Verification of Non-Linear Specifications for Neural Networks. - Chongli Qin; Krishnamurthy (Dj) Dvijotham; Brendan O'Donoghue; Rudy Bunel; Robert Stanforth; Sven Gowal; Jonathan Uesato; Grzegorz Swirszcz; Pushmeet Kohli (ICLR (Poster), 2019)

Sideways: Depth-Parallel Training of Video Models. - Mateusz Malinowski; Grzegorz Swirszcz; João Carreira 001; Viorica Patraucean (CVPR, 2020)

Gradient Forward-Propagation for Large-Scale Temporal Video Modelling. - Mateusz Malinowski; Dimitrios Vytiniotis; Grzegorz Swirszcz; Viorica Patraucean; João Carreira 001 (CVPR, 2021)

Rapid training of deep neural networks without skip connections or normalization layers using Deep Kernel Shaping. - James Martens; Andy Ballard; Guillaume Desjardins; Grzegorz Swirszcz; Valentin Dalibard; Jascha Sohl-Dickstein; Samuel S. Schoenholz (CoRR, 2021)

Discovering faster matrix multiplication algorithms with reinforcement learning. - Alhussein Fawzi; Matej Balog; Aja Huang; Thomas Hubert; Bernardino Romera-Paredes; Mohammadamin Barekatain; Alexander Novikov 001; Francisco J. R. Ruiz; Julian Schrittwieser; Grzegorz Swirszcz; David Silver; Demis Hassabis; et al. (Nat., 2022)

Stepping on the Edge: Curvature Aware Learning Rate Tuners. - Vincent Roulet; Atish Agarwala; Jean-Bastien Grill; Grzegorz Swirszcz; Mathieu Blondel; Fabian Pedregosa (NeurIPS, 2024)

Advancing Geometry with AI: Multi-agent Generation of Polytopes. - Grzegorz Swirszcz; Adam Zsolt Wagner; Geordie Williamson; Sam Blackwell; Bogdan Georgiev; Alex Davies; S. M. Ali Eslami; Sébastien Racanière; Theophane Weber; Pushmeet Kohli (CoRR, 2025)

Drums of high width. - Alex Davies; Prateek Gupta; Sébastien Racanière; Grzegorz Swirszcz; Adam Zsolt Wagner; Theophane Weber; Geordie Williamson (CoRR, 2025)