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收稿：2020-12-21，
修回：2020-12-23，
录用：2020-12-30，
纸质出版：2021-02-16
移动端阅览
神经信息处理系统大会（Conference on Neural Information Processing Systems，NeurIPS）是机器学习领域的顶级会议，在中国计算机学会（China Computer Federation，CCF）推荐国际学术会议中被评为人工智能领域的A类会议，一直广受关注。NeurIPS 2020收到了创纪录的9 467篇投稿，最终录用1 898篇论文。收录的论文涵盖了人工智能的各种主题，包括深度学习及其应用、强化学习与规划、纯理论研究、概率方法、优化及机器学习与社会等。本文回顾了NeurIPS 2020的亮点及论文录用情况，详细解读了特邀报告、最佳论文、口头报告及部分海报论文，希望能帮助读者快速了解NeurIPS 2020的盛况。
The Conference on Neural Information Processing Systems (NeurIPS)
as a top-tier conference in the field of machine learning and also a China Computer Federation(CCF)-A conference
has been receiving lots of attention. NeurIPS 2020 received a record-breaking 9 467 submissions
and finally accepted 1 898 papers
which covered various topics of artificial intelligence(AI)
such as deep learning and its applications
reinforcement learning and planning
theory
probabilistic methods
optimization
and the social aspect of machine learning. In this paper
we first reviewed the highlights and statistical information of NeurIPS 2020
for example
using GatherTown (each attendee is represented by a cartoon character) to improve the experience of immersive interactions with each other. Following that
we summarized the invited talks which covered multiple disciplines such as cryptography
feedback control theory
causal inference
and biology. Moreover
we provide a quick review of best papers
orals and some interesting posters
hoping to help readers have a quick glance over NeurIPS 2020.
Adlam B and Pennington J.2020. Understanding double descent requires a fine-grained bias-variance decomposition[EB/OL].[2020-12-20] . https://papers.nips.cc/paper/2020/file/7d420e2b2939762031eed0447a9be19f-Paper.pdf https://papers.nips.cc/paper/2020/file/7d420e2b2939762031eed0447a9be19f-Paper.pdf
Asi H and Duchi J C. 2020. Instance-optimality in Differential Privacy via Approximate Inverse Sensitivity Mechanisms.[EB/OL].[2020-12-20] . https://papers.nips.cc/paper/2020/file/a267f936e54d7c10a2bb70dbe6ad7a89-Paper.pdf https://papers.nips.cc/paper/2020/file/a267f936e54d7c10a2bb70dbe6ad7a89-Paper.pdf
Awasthi P, Jain H, Rawat A S and Vijayaraghavan A. 2020. Adversarial robustness via robust low rank representations[EB/OL].[2020-12-20] . https://papers.nips.cc/paper/2020/file/837a7924b8c0aa866e41b2721f66135c-Paper.pdf https://papers.nips.cc/paper/2020/file/837a7924b8c0aa866e41b2721f66135c-Paper.pdf
Bai S J, Koltun V and Kolter J Z.2020.Multiscale deep equilibrium models[EB/OL].[2020-12-20] . https://papers.nips.cc/paper/2020/file/3812f9a59b634c2a9c574610eaba5bed-Paper.pdf https://papers.nips.cc/paper/2020/file/3812f9a59b634c2a9c574610eaba5bed-Paper.pdf
Bear D M, Fan C F, Mrowca D, Li Y Z, Alter S, Nayebi A, Schwartz J, Li F F, Wu J J, Tenenbaum J B and Yamins D L K. 2020. Learning physical graph representations from visual scenes[EB/OL].[2020-12-20] . https://papers.nips.cc/paper/2020/file/4324e8d0d37b-110ee1a4f1633ac52df5-Paper.pdf https://papers.nips.cc/paper/2020/file/4324e8d0d37b-110ee1a4f1633ac52df5-Paper.pdf
Bechavod Y, Jung Cr and Wu Z W.2020.Metric-free individual fairness in online learning[EB/OL].[2020-12-20] . https://papers.nips.cc/paper/2020/file/80b618ebcac7aa97a6dac2ba65cb7e36-Paper.pdf https://papers.nips.cc/paper/2020/file/80b618ebcac7aa97a6dac2ba65cb7e36-Paper.pdf
Benton G, Finzi M, Izmailov P and Wilson A G. 2020. Learning Invariances in Neural Networks from Training Data.[EB/OL].[2020-12-20] . https://papers.nips.cc/paper/2020/file/cc8090c4d2791cdd9cd2cb3c24296190-Paper.pdf https://papers.nips.cc/paper/2020/file/cc8090c4d2791cdd9cd2cb3c24296190-Paper.pdf
Brown T B, Mann B, Ryder N, Subbiah M, Kaplan J, Dhariwal P, Neelakantan A, Shyam P, Sastry G, Askell A, Agarwal S, Herbert-Voss A, Krueger G, Henighan T, Child R, Ramesh A, Ziegler D M, Wu J, Winter C, Hesse C, Chen M, Sigler E, Litwin M, Gray S, Chess B, Clark J, Berner C, McCandlish S, Radford A, Sutskever I and Amodei D. 2020. Language Models are Few-Shot Learners[EB/OL].[2020-12-20] . https://papers.nips.cc/paper/2020/file/1457c0d6bfcb4967418bfb8ac142f64a-Paper.pdf https://papers.nips.cc/paper/2020/file/1457c0d6bfcb4967418bfb8ac142f64a-Paper.pdf
Celli A, Marchesi A, Farina G and Gatti N.2020. No-Regret Learning Dynamics for Extensive-Form Correlated Equilibrium[EB/OL].[2020-12-20] . https://papers.nips.cc/paper/2020/file/5763abe87ed1938799203fb6e8650025-Paper.pdf https://papers.nips.cc/paper/2020/file/5763abe87ed1938799203fb6e8650025-Paper.pdf
Chanpuriya S, Musco C, Sotiropoulos K and Tsourakakis C.2020. Node embeddings and exact low-rank representations of complex networks[EB/OL].[2020-12-20] . https://papers.nips.cc/paper/2020/file/99503bdd3c5a4c4671ada72d6fd81433-Paper.pdf https://papers.nips.cc/paper/2020/file/99503bdd3c5a4c4671ada72d6fd81433-Paper.pdf
Chelu V, Precup D and van Hasselt H. 2020. Forethought and hindsight in credit assignment[EB/OL].[2020-12-20] . https://papers.nips.cc/paper/2020/file/18064d61b6f93dab8681a460779b8429-Paper.pdf https://papers.nips.cc/paper/2020/file/18064d61b6f93dab8681a460779b8429-Paper.pdf
Chen L J, Zaharia M and Zou J.2020.FrugalML: how to use ML prediction APIs more accurately and cheaply[EB/OL].[2020-12-20] . https://papers.nips.cc/paper/2020/file/789ba2ae4d335e8a2ad-283a3f7effced-Paper.pdf https://papers.nips.cc/paper/2020/file/789ba2ae4d335e8a2ad-283a3f7effced-Paper.pdf
Chi L, Jiang B R and Mu Y D. 2020.Fast Fourier Convolution.[EB/OL].[2020-12-20] . https://papers.nips.cc/paper/2020/file/2fd5d41ec6cfab47e32164d5624269b1-Paper.pdf https://papers.nips.cc/paper/2020/file/2fd5d41ec6cfab47e32164d5624269b1-Paper.pdf
Dereziński M, Khanna R and Mahoney M W. 2020. Improved Guarantees and a Multiple-Descent Curve for Column Subset Selection and the Nyström Method[EB/OL].[2020-12-20] . https://papers.nips.cc/paper/2020/file/342c472b95d00421be10e9512b532866-Paper.pdf https://papers.nips.cc/paper/2020/file/342c472b95d00421be10e9512b532866-Paper.pdf
Dennis M, Jaques N, Vinitsky E, Bayen A, Russell S, Critch A and Levine S. 2020. Emergent Complexity and Zero-shot Transfer via Unsupervised Environment Design[EB/OL].[2020-12-20] . https://papers.nips.cc/paper/2020/file/985e9a46e10005356bbaf194249f6856-Paper.pdf https://papers.nips.cc/paper/2020/file/985e9a46e10005356bbaf194249f6856-Paper.pdf
Desai S, Durugkar I, Karnan H, Warnell G, Hanna J and Stone P. 2020. An imitation from observation approach to transfer learning with dynamics mismatch[EB/OL].[2020-12-20] . https://papers.nips.cc/paper/2020/file/28f248e9279ac845995c4e9f8af35c2b-Paper.pdf https://papers.nips.cc/paper/2020/file/28f248e9279ac845995c4e9f8af35c2b-Paper.pdf
Esteves C, Makadia A and Daniilidis K. 2020. Spin-weighted spherical CNNs[EB/OL].[2020-12-20] . https://papers.nips.cc/paper/2020/file/6217b2f7e4634fa665d31d3b4df81b56-Paper.pdf https://papers.nips.cc/paper/2020/file/6217b2f7e4634fa665d31d3b4df81b56-Paper.pdf
Evgenii C, Christophe D, Mohamed H, Luca O and Massimiliano P. Fair Regression via Plug-in Estimator and Recalibration with Statistical Guarantees.[EB/OL].[2020-12-20] . https://papers.nips.cc/paper/2020/file/ddd808772c035aed516d42ad3559be5f-Paper.pdf https://papers.nips.cc/paper/2020/file/ddd808772c035aed516d42ad3559be5f-Paper.pdf
Fan Z and Wang Z C. 2020. Spectra of the conjugate kernel and neural tangent kernel for linear-width neural networks[EB/OL].[2020-12-20] . https://papers.nips.cc/paper/2020/file/572201a4497b0b-9f02d4f279b09ec30d-Paper.pdf https://papers.nips.cc/paper/2020/file/572201a4497b0b-9f02d4f279b09ec30d-Paper.pdf
Feng W Z, Zhang J, Dong Y X, Han Y, Luan H B, Xu Q, Yang Q, Kharlamov E and Tang J. 2020. Graph random neural networks for semi-supervised learning on graphs[EB/OL].[2020-12-20] . https://arxiv.org/pdf/2005.11079.pdf https://arxiv.org/pdf/2005.11079.pdf
Fuchs F, Worrall D, Fischer V and Welling M.2020. SE(3)-transformers: 3D roto-translation equivariant attention networks[EB/OL].[2020-12-20] . https://papers.nips.cc/paper/2020/file/15231a7ce4ba789d13b722cc5c955834-Paper.pdf https://papers.nips.cc/paper/2020/file/15231a7ce4ba789d13b722cc5c955834-Paper.pdf
Galanti T and Wolf L.2020.On the modularity of hypernetworks[EB/OL].[2020-12-20] . https://papers.nips.cc/paper/2020/file/75c58d36157505a600e0695ed0b3a22d-Paper.pdf https://papers.nips.cc/paper/2020/file/75c58d36157505a600e0695ed0b3a22d-Paper.pdf
Gillen S, Jung C, Kearns M J and Roth A.2018. Online learning with an unknown fairness metric//Proceedings of Annual Conference on Neural Information Processing Systems. Montréal, Canada: ACM: 2605-2614
Grill J B, Strub F, AltchéF, Tallec C, Richemond P, Buchatskaya E, Doersch C, Pires B A, Guo D, Azar M G, Piot B, Kavukcuoglu K, Munos R and Valko M. 2020. Bootstrap your own latent-a new approach to self-supervised learning[EB/OL].[2020-12-20] . https://papers.nips.cc/paper/2020/file/f3ada80d5c4ee70142b17b8192b2958e-Paper.pdf https://papers.nips.cc/paper/2020/file/f3ada80d5c4ee70142b17b8192b2958e-Paper.pdf
Gupta G, Yadav K and Paull L.2020.La-MAML: look-ahead meta learning for continual learning[EB/OL].[2020-12-20] . https://papers.nips.cc/paper/2020/file/85b9a5ac91cd629bd3afe396ec07270a-Paper.pdf https://papers.nips.cc/paper/2020/file/85b9a5ac91cd629bd3afe396ec07270a-Paper.pdf
Ho J, Jain A and Abbeel P. 2020. Denoising diffusion probabilistic models[EB/OL].[2020-12-20] . https://papers.nips.cc/paper/2020/file/4c5bcfec8584af0d967f1ab10179ca4b-Paper.pdf https://papers.nips.cc/paper/2020/file/4c5bcfec8584af0d967f1ab10179ca4b-Paper.pdf
Huang Z Y, Hu P, Zhou J T Y, Lyu J C and Peng X. 2020. Partially View-aligned Clustering.[EB/OL].[2020-12-20] . https://papers.nips.cc/paper/2020/file/1e591403ff232de0f0f139ac51d99295-Paper.pdf https://papers.nips.cc/paper/2020/file/1e591403ff232de0f0f139ac51d99295-Paper.pdf
Jabri A, Owens A and Efros A A.2020.Space-time correspondence as a contrastive random walk[EB/OL].[2020-12-20] . https://papers.nips.cc/paper/2020/file/e2ef524fbf3d9fe611d5a8e90fefdc9c-Paper.pdff https://papers.nips.cc/paper/2020/file/e2ef524fbf3d9fe611d5a8e90fefdc9c-Paper.pdff
Jenrungrot T, Jayaram V, Seitz S and Kemelmacher-Shlizerman I.2020.The cone of silence: speech separation by localization[EB/OL] .[2020-12-20]. https://papers.nips.cc/paper/2020/file/f056bfa71038e04a2400266027c169f9-Paper.pdf https://papers.nips.cc/paper/2020/file/f056bfa71038e04a2400266027c169f9-Paper.pdf
Kang G L, Wei Y C, Yang Y, Zhuang Y T and Hauptmann A G.2020.Pixel-level cycle association: a new perspective for domain adaptive semantic segmentation[EB/OL].[2020-12-20] . https://papers.nips.cc/paper/2020/file/243be2818a23c980ad664f30f48e5d19-Paper.pdf https://papers.nips.cc/paper/2020/file/243be2818a23c980ad664f30f48e5d19-Paper.pdf
Karakida R and Osawa K. 2020. Understanding approximate Fisher information for fast convergence of natural gradient descent in wide neural networks[EB/OL].[2020-12-20] . https://papers.nips.cc/paper/2020/file/7b41bfa5085806dfa24b8c9de0ce567f-Paper.pdf https://papers.nips.cc/paper/2020/file/7b41bfa5085806dfa24b8c9de0ce567f-Paper.pdf
Karalias N and Loukas A.2020. Erdös Goes Neural: an unsupervised learning framework for combinatorial optimization on graphs.[EB/OL].[2020-12-20] . https://papers.nips.cc/paper/2020/file/49f85a9ed090b20c8bed85a5923c669f-Paper.pdf https://papers.nips.cc/paper/2020/file/49f85a9ed090b20c8bed85a5923c669f-Paper.pdf
Karras T, Aittala M, Hellsten J, Laine S, Lehtinen and Aila T.2020. Training generative adversarial networks with limited data.[EB/OL].[2020-12-20] . https://papers.nips.cc/paper/2020/file/8d30aa96e72440759f74bd2306c1fa3d-Paper.pdf https://papers.nips.cc/paper/2020/file/8d30aa96e72440759f74bd2306c1fa3d-Paper.pdf
Kim J, Kim S, Kong J and Yoon S.2020.Glow-TTS: A generative flow for text-to-speech via monotonic alignment search[EB/OL].[2020-12-20] . https://papers.nips.cc/paper/2020/file/5c3b99e8f92532e5ad1556e53ceea00c-Paper.pdf https://papers.nips.cc/paper/2020/file/5c3b99e8f92532e5ad1556e53ceea00c-Paper.pdf
Lee K, Lee Byeong-Uk, Shin U and Kweon In So. 2020. An efficient asynchronous method for integrating evolutionary and gradient-based policy search[EB/OL].[2020-12-20] . https://papers.nips.cc/paper/2020/file/731309c4bb223491a9f67eac5214fb2e-Paper.pdf https://papers.nips.cc/paper/2020/file/731309c4bb223491a9f67eac5214fb2e-Paper.pdf
Lee W, Yu H, Rival X and Yang H.2020. On correctness of automatic differentiation for non-differentiable functions[EB/OL].[2020-12-20] . https://papers.nips.cc/paper/2020/file/4aaa76178f8567e05c8e8295c96171d8-Paper.pdf https://papers.nips.cc/paper/2020/file/4aaa76178f8567e05c8e8295c96171d8-Paper.pdf
Lewkowycz A and Gur-Ari G. 2020. On the training dynamics of deep networks with L 2 regularization[EB/OL].[2020-12-20] . https://papers.nips.cc/paper/2020/file/32fcc8cfe1fa4c77b5c58dafd36d1a98-Paper.pdf https://papers.nips.cc/paper/2020/file/32fcc8cfe1fa4c77b5c58dafd36d1a98-Paper.pdf .
Li M, Chen S H, Zhang Y and Tsang I.2020. Graph cross networks with vertex infomax pooling[EB/OL].[2020-12-20] . https://papers.nips.cc/paper/2020/file/a26398dca6f47b49876cbaffbc9954f9-Paper.pdf https://papers.nips.cc/paper/2020/file/a26398dca6f47b49876cbaffbc9954f9-Paper.pdf
Liao Z Y, Couillet R and Mahoney M W.2020.A random matrix analysis of random fourier features: beyond the Gaussian kernel, a precise phase transition, and the corresponding double descent[EB/OL].[2020-12-20] . https://papers.nips.cc/paper/2020/file/a03fa30821986dff10fc66647c84c9c3-Paper.pdf https://papers.nips.cc/paper/2020/file/a03fa30821986dff10fc66647c84c9c3-Paper.pdf
Liu C, Salzmann M, Lin T, Tomioka R and Süsstrunk S.2020. On the loss landscape of adversarial training: identifying challenges and how to overcome them[EB/OL].[2020-12-20] . https://papers.nips.cc/paper/2020/file/f56d8183992b6c54c92c16a8519a6e2b-Paper.pdf https://papers.nips.cc/paper/2020/file/f56d8183992b6c54c92c16a8519a6e2b-Paper.pdf
Morvan M L, Josse J, Moreau T, Scornet E and Varoquaux G.2020.NeuMiss networks: differentiable programming for supervised learning with missing values[EB/OL].[2020-12-20] . https://papers.nips.cc/paper/2020/file/42ae1544956fbe6e09242-e6cd752444c-Paper.pdf https://papers.nips.cc/paper/2020/file/42ae1544956fbe6e09242-e6cd752444c-Paper.pdf
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Mu J and Andreas J. 2020. Compositional explanations of neurons[EB/OL].[2020-12-20] . https://papers.nips.cc/paper/2020/file/c74956ffb38ba48ed6ce977af6727275-Paper.pdf https://papers.nips.cc/paper/2020/file/c74956ffb38ba48ed6ce977af6727275-Paper.pdf
Lawrence N, Loewen P, Forbes M, Backstrom and Gopaluni B.2020. Almost Surely Stable Deep Dynamics[EB/OL].[2020-12-20] . https://papers.nips.cc/paper/2020/file/daecf755df5b1d637033bb29b319c39a-Paper.pdf https://papers.nips.cc/paper/2020/file/daecf755df5b1d637033bb29b319c39a-Paper.pdf
Pan P B, Swaroop S, Immer A, Eschenhagen R, Turner R E and Khan M E.2020.Continual deep learning by functional regularisation of memorable past[EB/OL].[2020-12-20] . https://papers.nips.cc/paper/2020/file/2f3bbb9730639e9ea48f309d9a79ff01-Paper.pdf https://papers.nips.cc/paper/2020/file/2f3bbb9730639e9ea48f309d9a79ff01-Paper.pdf
Peng D Y, Dong X Y, Real E, Tan M X, Lu Y F, Bender G, Liu H X, Kraft A, Liang C and Le Q V. 2020. PyGlove: Symbolic Programming for Automated Machine Learning.[EB/OL].[2020-12-20] . https://papers.nips.cc/paper/2020/file/012a91467f210472fab4e11359bbfef6-Paper.pdf https://papers.nips.cc/paper/2020/file/012a91467f210472fab4e11359bbfef6-Paper.pdf
Pinheiro P O, Almahairi A, Benmalek R Y, Golemo F and Courville A. 2020. Unsupervised learning of dense visual representations[EB/OL].[2020-12-20] . https://papers.nips.cc/paper/2020/file/3000311ca56a1cb93397bc676c0b7fff-Paper.pdf https://papers.nips.cc/paper/2020/file/3000311ca56a1cb93397bc676c0b7fff-Paper.pdf
Rashidinejad P, Jiao J T and Russel S.2020.SLIP: learning to predict in unknown dynamical systems with long-term memory[EB/OL].[2020-12-20] . https://papers.nips.cc/paper/2020/file/3e91970f771a2c473ae36b60d1146068-Paper.pdf https://papers.nips.cc/paper/2020/file/3e91970f771a2c473ae36b60d1146068-Paper.pdf
Salman H, Ilyas A, Engstrom L, Kapoor A and Madry A.2020.Do adversarially robust ImageNet models transfer better?[EB/OL].[2020-12-20] . https://papers.nips.cc/paper/2020/file/24357dd085d2c4b1a88a7e0692e60294-Paper.pdf https://papers.nips.cc/paper/2020/file/24357dd085d2c4b1a88a7e0692e60294-Paper.pdf
Seshadhri C, Sharma A, Stolman A and Goel A. 2020. The impossibility of low-rank representations for triangle-rich complex networks//Proceedings of the National Academy of Sciences, 117(11): 5631-5637
Shao J, Hu K, Wang C H, Xue X Y and Raj B. 2020. Is normalization indispensable for training deep neural network?[EB/OL].[2020-12-20] . https://papers.nips.cc/paper/2020/file/9b8619251a19057cff70779273e95aa6-Paper.pdf https://papers.nips.cc/paper/2020/file/9b8619251a19057cff70779273e95aa6-Paper.pdf
Sitzmann V, Martel J N P, Bergman A W, Lindell D B and Wetzstein G.2020.Implicit neural representations with periodic activation functions[EB/OL].[2020-12-20] . https://papers.nips.cc/paper/2020/file/53c04118df112c13a8c34b38343b9c10-Paper.pdf https://papers.nips.cc/paper/2020/file/53c04118df112c13a8c34b38343b9c10-Paper.pdf
Song J M and Ermon S.2020.Multi-label contrastive predictive coding[EB/OL].[2020-12-20] . https://papers.nips.cc/paper/2020/file/5cd5058bca53951ffa7801bcdf421651-Paper.pdf https://papers.nips.cc/paper/2020/file/5cd5058bca53951ffa7801bcdf421651-Paper.pdf
Tang K H, Huang J Q and Zhang H W. 2020. Long-tailed classification by keeping the good and removing the bad momentum causal effect[EB/OL].[2020-12-20] . https://papers.nips.cc/paper/2020/file/1091660f3dff84fd648efe31391c5524-Paper.pdf https://papers.nips.cc/paper/2020/file/1091660f3dff84fd648efe31391c5524-Paper.pdf
Tao R Y, François-Lavet V and Pineau J.2020. Novelty search in representational space for sample efficient exploration[EB/OL].[2020-12-20] . https://papers.nips.cc/paper/2020/file/5ca41a86596a5ed567d15af0be224952-Paper.pdf https://papers.nips.cc/paper/2020/file/5ca41a86596a5ed567d15af0be224952-Paper.pdf
Tatro N, Chen P Y, Das P, Melnyk I, Sattigeri P and Lai R.2020. Optimizing mode connectivity via neuron alignment[EB/OL].[2020-12-20] . https://papers.nips.cc/paper/2020/file/aecad42329922dfc97eee948606e1f8e-Paper.pdf https://papers.nips.cc/paper/2020/file/aecad42329922dfc97eee948606e1f8e-Paper.pdf
Teshima T, Ishikawa I, Tojo K, Oono K, Ikeda M and Sugiyama M.2020. Coupling-based invertible neural networks are universal diffeomorphism approximators[EB/OL].[2020-12-20] . https://papers.nips.cc/paper/2020/file/2290a7385ed77cc5592dc2153229f-082-Paper.pdf https://papers.nips.cc/paper/2020/file/2290a7385ed77cc5592dc2153229f-082-Paper.pdf
Udrescu S M, Tan A, Feng J H, Neto O, Wu T L and Tegmark M.2020.AI Feynman 2.0: pareto-optimal symbolic regression exploiting graph modularity[EB/OL].[2020-12-20] . https://papers.nips.cc/paper/2020/file/33a854e247155d590883b93bca53848a-Paper.pdf https://papers.nips.cc/paper/2020/file/33a854e247155d590883b93bca53848a-Paper.pdf
Vialard F X, Kwitt R, Wei S and Niethammer M. 2020. A shooting formulation of deep learning[EB/OL].[2020-12-20] . https://papers.nips.cc/paper/2020/file/89562dccfeb1d0394b9ae7e09544dc70-Paper.pdf https://papers.nips.cc/paper/2020/file/89562dccfeb1d0394b9ae7e09544dc70-Paper.pdf
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