|
| 1 | +@inproceedings{Agarwal.2022, |
| 2 | + title = {OpenXAI: Towards a Transparent Evaluation of Model Explanations}, |
| 3 | + author = {Chirag Agarwal and Satyapriya Krishna and Eshika Saxena and Martin Pawelczyk and Nari Johnson and Isha Puri and Marinka Zitnik and Himabindu Lakkaraju}, |
| 4 | + year = {2022}, |
| 5 | + booktitle = {Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022 ({NeurIPS} 2022)}, |
| 6 | + url = {http://papers.nips.cc/paper\_files/paper/2022/hash/65398a0eba88c9b4a1c38ae405b125ef-Abstract-Datasets\_and\_Benchmarks.html} |
| 7 | +} |
| 8 | +@article{Alber.2019, |
| 9 | + title = {iNNvestigate Neural Networks!}, |
| 10 | + author = {Maximilian Alber and Sebastian Lapuschkin and Philipp Seegerer and Miriam H{\"{a}}gele and Kristof T. Sch{\"{u}}tt and Gr{\'{e}}goire Montavon and Wojciech Samek and Klaus{-}Robert M{\"{u}}ller and Sven D{\"{a}}hne and Pieter{-}Jan Kindermans}, |
| 11 | + year = {2019}, |
| 12 | + journal = {J. Mach. Learn. Res.}, |
| 13 | + volume = {20}, |
| 14 | + pages = {93:1--93:8}, |
| 15 | + url = {https://jmlr.org/papers/v20/18-540.html} |
| 16 | +} |
| 17 | +@article{Arya.2020, |
| 18 | + title = {{AI} Explainability 360: An Extensible Toolkit for Understanding Data and Machine Learning Models}, |
| 19 | + author = {Vijay Arya and Rachel K. E. Bellamy and Pin{-}Yu Chen and Amit Dhurandhar and Michael Hind and Samuel C. Hoffman and Stephanie Houde and Q. Vera Liao and Ronny Luss and Aleksandra Mojsilovic and Sami Mourad and Pablo Pedemonte and Ramya Raghavendra and John T. Richards and Prasanna Sattigeri and Karthikeyan Shanmugam and Moninder Singh and Kush R. Varshney and Dennis Wei and Yunfeng Zhang}, |
| 20 | + year = {2020}, |
| 21 | + journal = {J. Mach. Learn. Res.}, |
| 22 | + volume = {21}, |
| 23 | + pages = {130:1--130:6}, |
| 24 | + url = {https://jmlr.org/papers/v21/19-1035.html} |
| 25 | +} |
| 26 | +@article{Baniecki.2021, |
| 27 | + title = {dalex: Responsible Machine Learning with Interactive Explainability and Fairness in Python}, |
| 28 | + author = {Hubert Baniecki and Wojciech Kretowicz and Piotr Piatyszek and Jakub Wisniewski and Przemyslaw Biecek}, |
| 29 | + year = {2021}, |
| 30 | + journal = {J. Mach. Learn. Res.}, |
| 31 | + volume = {22}, |
| 32 | + pages = {214:1--214:7}, |
| 33 | + url = {https://jmlr.org/papers/v22/20-1473.html} |
| 34 | +} |
| 35 | +@inproceedings{Bischl.2021, |
| 36 | + title = {OpenML Benchmarking Suites}, |
| 37 | + author = {Bernd Bischl and Giuseppe Casalicchio and Matthias Feurer and Pieter Gijsbers and Frank Hutter and Michel Lang and Rafael Gomes Mantovani and Jan N. van Rijn and Joaquin Vanschoren}, |
| 38 | + year = {2021}, |
| 39 | + booktitle = {Proceedings of the Neural Information Processing Systems Track on Datasets and Benchmarks 1 ({NeurIPS} 2021)}, |
| 40 | + url = {https://datasets-benchmarks-proceedings.neurips.cc/paper/2021/hash/c7e1249ffc03eb9ded908c236bd1996d-Abstract-round2.html} |
| 41 | +} |
| 42 | +@inproceedings{Bordt.2023, |
| 43 | + title = {From Shapley Values to Generalized Additive Models and back}, |
| 44 | + author = {Sebastian Bordt and Ulrike von Luxburg}, |
| 45 | + year = {2023}, |
| 46 | + booktitle = {International Conference on Artificial Intelligence and Statistics ({AISTATS} 2023)}, |
| 47 | + publisher = {{PMLR}}, |
| 48 | + series = {Proceedings of Machine Learning Research}, |
| 49 | + volume = {206}, |
| 50 | + pages = {709--745}, |
| 51 | + url = {https://proceedings.mlr.press/v206/bordt23a.html} |
| 52 | +} |
| 53 | +@inproceedings{Covert.2021, |
| 54 | + title = {Improving KernelSHAP: Practical Shapley Value Estimation Using Linear Regression}, |
| 55 | + author = {Ian Covert and Su{-}In Lee}, |
| 56 | + year = {2021}, |
| 57 | + booktitle = {The 24th International Conference on Artificial Intelligence and Statistics ({AISTATS} 2021)}, |
| 58 | + publisher = {{PMLR}}, |
| 59 | + series = {Proceedings of Machine Learning Research}, |
| 60 | + volume = {130}, |
| 61 | + pages = {3457--3465}, |
| 62 | + url = {http://proceedings.mlr.press/v130/covert21a.html} |
| 63 | +} |
| 64 | +@inproceedings{Fumagalli.2023, |
| 65 | + title = {{SHAP-IQ:} Unified Approximation of any-order Shapley Interactions}, |
| 66 | + author = {Fabian Fumagalli and Maximilian Muschalik and Patrick Kolpaczki and Eyke H{\"{u}}llermeier and Barbara Hammer}, |
| 67 | + year = {2023}, |
| 68 | + booktitle = {Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, ({NeurIPS} 2023)}, |
| 69 | + url = {http://papers.nips.cc/paper\_files/paper/2023/hash/264f2e10479c9370972847e96107db7f-Abstract-Conference.html} |
| 70 | +} |
| 71 | +@inproceedings{Fumagalli.2024, |
| 72 | + title = {KernelSHAP-IQ: Weighted Least Square Optimization for Shapley Interactions}, |
| 73 | + author = {Fabian Fumagalli and Maximilian Muschalik and Patrick Kolpaczki and Eyke H{\"{u}}llermeier and Barbara Hammer}, |
| 74 | + year = {2024}, |
| 75 | + booktitle = {Forty-first International Conference on Machine Learning ({ICML} 2024)}, |
| 76 | + publisher = {OpenReview.net}, |
| 77 | + url = {https://openreview.net/forum?id=d5jXW2H4gg} |
| 78 | +} |
| 79 | +@inproceedings{Harris.2022, |
| 80 | + title = {Joint Shapley values: a measure of joint feature importance}, |
| 81 | + author = {Chris Harris and Richard Pymar and Colin Rowat}, |
| 82 | + year = {2022}, |
| 83 | + booktitle = {The Tenth International Conference on Learning Representations ({ICLR} 2022)}, |
| 84 | + publisher = {OpenReview.net}, |
| 85 | + url = {https://openreview.net/forum?id=vcUmUvQCloe} |
| 86 | +} |
| 87 | +@article{Hedstrom.2023, |
| 88 | + title = {Quantus: An Explainable {AI} Toolkit for Responsible Evaluation of Neural Network Explanations and Beyond}, |
| 89 | + author = {Anna Hedstr{\"{o}}m and Leander Weber and Daniel Krakowczyk and Dilyara Bareeva and Franz Motzkus and Wojciech Samek and Sebastian Lapuschkin and Marina M.{-}C. H{\"{o}}hne}, |
| 90 | + year = {2023}, |
| 91 | + journal = {J. Mach. Learn. Res.}, |
| 92 | + volume = {24}, |
| 93 | + pages = {34:1--34:11}, |
| 94 | + url = {https://jmlr.org/papers/v24/22-0142.html} |
| 95 | +} |
| 96 | +@inproceedings{Jiang.2023, |
| 97 | + title = {OpenDataVal: a Unified Benchmark for Data Valuation}, |
| 98 | + author = {Kevin Fu Jiang and Weixin Liang and James Y. Zou and Yongchan Kwon}, |
| 99 | + year = {2023}, |
| 100 | + booktitle = {Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023 ({NeurIPS} 2023)}, |
| 101 | + url = {http://papers.nips.cc/paper\_files/paper/2023/hash/5b047c7d862059a5df623c1ce2982fca-Abstract-Datasets\_and\_Benchmarks.html} |
| 102 | +} |
| 103 | +@article{Klaise.2021, |
| 104 | + title = {Alibi Explain: Algorithms for Explaining Machine Learning Models}, |
| 105 | + author = {Janis Klaise and Arnaud Van Looveren and Giovanni Vacanti and Alexandru Coca}, |
| 106 | + year = {2021}, |
| 107 | + journal = {J. Mach. Learn. Res.}, |
| 108 | + volume = {22}, |
| 109 | + pages = {181:1--181:7}, |
| 110 | + url = {https://jmlr.org/papers/v22/21-0017.html} |
| 111 | +} |
| 112 | +@article{Kokhlikyan.2020, |
| 113 | + title = {Captum: {A} unified and generic model interpretability library for PyTorch}, |
| 114 | + author = {Narine Kokhlikyan and Vivek Miglani and Miguel Martin and Edward Wang and Bilal Alsallakh and Jonathan Reynolds and Alexander Melnikov and Natalia Kliushkina and Carlos Araya and Siqi Yan and Orion Reblitz{-}Richardson}, |
| 115 | + year = {2020}, |
| 116 | + journal = {CoRR}, |
| 117 | + volume = {abs/2009.07896}, |
| 118 | + url = {https://arxiv.org/abs/2009.07896}, |
| 119 | + eprinttype = {arXiv}, |
| 120 | + eprint = {2009.07896} |
| 121 | +} |
| 122 | +@inproceedings{Kolpaczki.2024a, |
| 123 | + title = {Approximating the Shapley Value without Marginal Contributions}, |
| 124 | + author = {Patrick Kolpaczki and Viktor Bengs and Maximilian Muschalik and Eyke H{\"{u}}llermeier}, |
| 125 | + year = {2024}, |
| 126 | + booktitle = {Thirty-Eighth {AAAI} Conference on Artificial Intelligence, ({AAAI} 2024)}, |
| 127 | + publisher = {{AAAI} Press}, |
| 128 | + pages = {13246--13255}, |
| 129 | + doi = {10.1609/AAAI.V38I12.29225} |
| 130 | +} |
| 131 | +@inproceedings{Kolpaczki.2024b, |
| 132 | + title = {{SVARM-IQ:} Efficient Approximation of Any-order Shapley Interactions through Stratification}, |
| 133 | + author = {Patrick Kolpaczki and Maximilian Muschalik and Fabian Fumagalli and Barbara Hammer and Eyke H{\"{u}}llermeier}, |
| 134 | + year = {2024}, |
| 135 | + booktitle = {International Conference on Artificial Intelligence and Statistics ({AISTATS} 2024)}, |
| 136 | + publisher = {{PMLR}}, |
| 137 | + series = {Proceedings of Machine Learning Research}, |
| 138 | + volume = {238}, |
| 139 | + pages = {3520--3528}, |
| 140 | + url = {https://proceedings.mlr.press/v238/kolpaczki24a.html} |
| 141 | +} |
| 142 | +@inproceedings{Li.2023, |
| 143 | + title = {M\({}^{\mbox{4}}\): {A} Unified {XAI} Benchmark for Faithfulness Evaluation of Feature Attribution Methods across Metrics, Modalities and Models}, |
| 144 | + author = {Xuhong Li and Mengnan Du and Jiamin Chen and Yekun Chai and Himabindu Lakkaraju and Haoyi Xiong}, |
| 145 | + year = {2023}, |
| 146 | + booktitle = {Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023 ({NeurIPS} 2023)}, |
| 147 | + url = {http://papers.nips.cc/paper\_files/paper/2023/hash/05957c194f4c77ac9d91e1374d2def6b-Abstract-Datasets\_and\_Benchmarks.html} |
| 148 | +} |
| 149 | +@inproceedings{Liu.2021, |
| 150 | + title = {Synthetic Benchmarks for Scientific Research in Explainable Machine Learning}, |
| 151 | + author = {Yang Liu and Sujay Khandagale and Colin White and Willie Neiswanger}, |
| 152 | + year = {2021}, |
| 153 | + booktitle = {Proceedings of the Neural Information Processing Systems Track on Datasets and Benchmarks 1 ({NeurIPS} 2021)}, |
| 154 | + url = {https://datasets-benchmarks-proceedings.neurips.cc/paper/2021/hash/c16a5320fa475530d9583c34fd356ef5-Abstract-round2.html} |
| 155 | +} |
| 156 | +@inproceedings{Lundberg.2017, |
| 157 | + title = {A Unified Approach to Interpreting Model Predictions}, |
| 158 | + author = {Scott M. Lundberg and Su{-}In Lee}, |
| 159 | + year = {2017}, |
| 160 | + booktitle = {Advances in Neural Information Processing Systems 30: Annual Conference on Neural Information Processing Systems 2017, December 4-9, 2017, Long Beach, CA, {USA}}, |
| 161 | + pages = {4765--4774}, |
| 162 | + url = {https://proceedings.neurips.cc/paper/2017/hash/8a20a8621978632d76c43dfd28b67767-Abstract.html} |
| 163 | +} |
| 164 | +@article{Lundberg.2020, |
| 165 | + title = {From local explanations to global understanding with explainable {AI} for trees}, |
| 166 | + author = {Scott M. Lundberg and Gabriel G. Erion and Hugh Chen and Alex J. DeGrave and Jordan M. Prutkin and Bala Nair and Ronit Katz and Jonathan Himmelfarb and Nisha Bansal and Su{-}In Lee}, |
| 167 | + year = {2020}, |
| 168 | + journal = {Nat. Mach. Intell.}, |
| 169 | + volume = {2}, |
| 170 | + number = {1}, |
| 171 | + pages = {56--67}, |
| 172 | + doi = {10.1038/S42256-019-0138-9} |
| 173 | +} |
| 174 | +@inproceedings{Muschalik.2024a, |
| 175 | + title = {Beyond TreeSHAP: Efficient Computation of Any-Order Shapley Interactions for Tree Ensembles}, |
| 176 | + author = {Maximilian Muschalik and Fabian Fumagalli and Barbara Hammer and Eyke H{\"{u}}llermeier}, |
| 177 | + year = {2024}, |
| 178 | + booktitle = {Thirty-Eighth {AAAI} Conference on Artificial Intelligence, ({AAAI} 2024)}, |
| 179 | + publisher = {{AAAI} Press}, |
| 180 | + pages = {14388--14396}, |
| 181 | + doi = {10.1609/AAAI.V38I13.29352} |
| 182 | +} |
| 183 | +@inproceedings{Muschalik.2024b, |
| 184 | + title = {shapiq: Shapley Interactions for Machine Learning}, |
| 185 | + author = {Maximilian Muschalik and Hubert Baniecki and Fabian Fumagalli and Patrick Kolpaczki and Barbara Hammer and Eyke H{\"{u}}llermeier}, |
| 186 | + year = {2024}, |
| 187 | + booktitle = {Advances in Neural Information Processing Systems 38: Annual Conference on Neural Information Processing Systems 2024, ({NeurIPS} 2024)}, |
| 188 | + url = {http://papers.nips.cc/paper\_files/paper/2024/hash/eb3a9313405e2d4175a5a3cfcd49999b-Abstract-Datasets\_and\_Benchmarks\_Track.html} |
| 189 | +} |
| 190 | +@article{Olsen.2024, |
| 191 | + title = {A comparative study of methods for estimating model-agnostic Shapley value explanations}, |
| 192 | + author = {Lars Henry Berge Olsen and Ingrid Kristine Glad and Martin Jullum and Kjersti Aas}, |
| 193 | + year = {2024}, |
| 194 | + journal = {Data Min. Knowl. Discov.}, |
| 195 | + volume = {38}, |
| 196 | + number = {4}, |
| 197 | + pages = {1782--1829}, |
| 198 | + doi = {10.1007/S10618-024-01016-Z} |
| 199 | +} |
| 200 | +@article{Pelegrina.2023, |
| 201 | + title = {A \emph{k}-additive Choquet integral-based approach to approximate the {SHAP} values for local interpretability in machine learning}, |
| 202 | + author = {Guilherme Dean Pelegrina and Leonardo Tomazeli Duarte and Michel Grabisch}, |
| 203 | + year = {2023}, |
| 204 | + journal = {Artif. Intell.}, |
| 205 | + volume = {325}, |
| 206 | + pages = {104014}, |
| 207 | + doi = {10.1016/J.ARTINT.2023.104014} |
| 208 | +} |
| 209 | +@inproceedings{Sundararajan.2020, |
| 210 | + title = {The Shapley Taylor Interaction Index}, |
| 211 | + author = {Mukund Sundararajan and Kedar Dhamdhere and Ashish Agarwal}, |
| 212 | + year = {2020}, |
| 213 | + booktitle = {Proceedings of the 37th International Conference on Machine Learning ({ICML} 2020)}, |
| 214 | + publisher = {{PMLR}}, |
| 215 | + series = {Proceedings of Machine Learning Research}, |
| 216 | + volume = {119}, |
| 217 | + pages = {9259--9268}, |
| 218 | + url = {http://proceedings.mlr.press/v119/sundararajan20a.html} |
| 219 | +} |
| 220 | +@article{Tsai.2023, |
| 221 | + title = {Faith-Shap: The Faithful Shapley Interaction Index}, |
| 222 | + author = {Che{-}Ping Tsai and Chih{-}Kuan Yeh and Pradeep Ravikumar}, |
| 223 | + year = {2023}, |
| 224 | + journal = {J. Mach. Learn. Res.}, |
| 225 | + volume = {24}, |
| 226 | + pages = {94:1--94:42}, |
| 227 | + url = {https://jmlr.org/papers/v24/22-0202.html} |
| 228 | +} |
| 229 | +@inproceedings{Yu.2022, |
| 230 | + title = {Linear tree shap}, |
| 231 | + author = {Peng Yu and Albert Bifet and Jesse Read and Chao Xu}, |
| 232 | + year = {2022}, |
| 233 | + booktitle = {Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022 ({NeurIPS} 2022)}, |
| 234 | + url = {http://papers.nips.cc/paper\_files/paper/2022/hash/a5a3b1ef79520b7cd122d888673a3ebc-Abstract-Conference.html} |
| 235 | +} |
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