More from the Same Authors

• 2021 Spotlight: Lower and Upper Bounds on the Pseudo-Dimension of Tensor Network Models »
  Behnoush Khavari · Guillaume Rabusseau
• 2021 Spotlight: Continuous vs. Discrete Optimization of Deep Neural Networks »
  Omer Elkabetz · Nadav Cohen
• 2021 : GPU-Podracer: Scalable and Elastic Library for Cloud-Native Deep Reinforcement Learning »
  Xiao-Yang Liu · Zhuoran Yang · Zhaoran Wang · Anwar Walid · Jian Guo · Michael Jordan
• 2021 : Few Shot Image Generation via Implicit Autoencoding of Support Sets »
  Shenyang Huang · Kuan-Chieh Wang · Guillaume Rabusseau · Alireza Makhzani
• 2021 : Graph-Tensor Singular Value Decomposition for Data Recovery »
  Lei Deng · Haifeng Zheng · Xiao-Yang Liu
• 2021 : High Performance Hierarchical Tucker Tensor Learning Using GPU Tensor Cores »
  hao huang · Xiao-Yang Liu · Weiqin Tong · Tao Zhang · Anwar Walid
• 2021 : Codee: A Tensor Embedding Scheme for Binary Code Search »
  Jia Yang · Cai Fu · Xiao-Yang Liu
• 2021 : Deep variational reinforcement learning by optimizing Hamiltonian equation »
  Zeliang Zhang · Xiao-Yang Liu
• 2021 : Spectral Tensor Layer for Model-Parallel Deep Neural Networks »
  Zhiyuan Wang · Xiao-Yang Liu
• 2022 Poster: TTOpt: A Maximum Volume Quantized Tensor Train-based Optimization and its Application to Reinforcement Learning »
  Konstantin Sozykin · Andrei Chertkov · Roman Schutski · Anh-Huy Phan · Andrzej S CICHOCKI · Ivan Oseledets
• 2023 Poster: Neural Harmonics: Bridging Spectral Embedding and Matrix Completion in Self-Supervised Learning »
  Marina Munkhoeva · Ivan Oseledets
• 2023 Poster: On the Ability of Graph Neural Networks to Model Interactions Between Vertices »
  Noam Razin · Tom Verbin · Nadav Cohen
• 2023 Poster: PROTES: Probabilistic Optimization with Tensor Sampling »
  Anastasiia Batsheva · Andrei Chertkov · Gleb Ryzhakov · Ivan Oseledets
• 2023 Poster: What Makes Data Suitable for a Locally Connected Neural Network? A Necessary and Sufficient Condition Based on Quantum Entanglement. »
  ‪Yotam Alexander‬‏ · Nimrod De La Vega · Noam Razin · Nadav Cohen
• 2023 Poster: Classical Simulation of Quantum Circuits: Parallel Environments and Benchmark »
  Xiao-Yang Liu · Zeliang Zhang
• 2022 Poster: Smoothed Embeddings for Certified Few-Shot Learning »
  Mikhail Pautov · Olesya Kuznetsova · Nurislam Tursynbek · Aleksandr Petiushko · Ivan Oseledets
• 2022 Poster: Homomorphic Matrix Completion »
  Xiao-Yang Liu · Zechu (Steven) Li · Xiaodong Wang
• 2022 Poster: FinRL-Meta: Market Environments and Benchmarks for Data-Driven Financial Reinforcement Learning »
  Xiao-Yang Liu · Ziyi Xia · Jingyang Rui · Jiechao Gao · Hongyang Yang · Ming Zhu · Christina Wang · Zhaoran Wang · Jian Guo
• 2021 : Discussion Pannel »
  Xiao-Yang Liu · Qibin Zhao · Chao Li · Guillaume Rabusseau
• 2021 : Nadav Cohen »
  Nadav Cohen
• 2021 : Implicit Regularization in Quantum Tensor Networks »
  Nadav Cohen
• 2021 : High Performance Computation for Tensor Networks Learning »
  Anwar Walid · Xiao-Yang Liu
• 2021 Workshop: Second Workshop on Quantum Tensor Networks in Machine Learning »
  Xiao-Yang Liu · Qibin Zhao · Ivan Oseledets · Yufei Ding · Guillaume Rabusseau · Jean Kossaifi · Khadijeh Najafi · Anwar Walid · Andrzej Cichocki · Masashi Sugiyama
• 2021 : Opening Remarks »
  Xiao-Yang Liu
• 2021 Poster: Lower and Upper Bounds on the Pseudo-Dimension of Tensor Network Models »
  Behnoush Khavari · Guillaume Rabusseau
• 2021 Poster: Continuous vs. Discrete Optimization of Deep Neural Networks »
  Omer Elkabetz · Nadav Cohen
• 2020 : Closing Remarks »
  Xiao-Yang Liu
• 2020 : Invited Talk 9 Q&A by Guillaume »
  Guillaume Rabusseau
• 2020 : Invited Talk 9: Tensor Network Models for Structured Data »
  Guillaume Rabusseau
• 2020 : Panel Discussion 2: Software and High Performance Implementation »
  Glen Evenbly · Martin Ganahl · Paul Springer · Xiao-Yang Liu
• 2020 : Invited Talk 4 Q&A by Ivan »
  Ivan Oseledets
• 2020 : Invited Talk 4: Quantum in ML and ML in Quantum »
  Ivan Oseledets
• 2020 : Invited Talk 2 Q&A by Cohen »
  Nadav Cohen
• 2020 : Invited Talk 2: Expressiveness in Deep Learning via Tensor Networks and Quantum Entanglement »
  Nadav Cohen
• 2020 : Invited Talk 1 Q&A by Jens »
  Jens Eisert
• 2020 : Invited Talk 1: Tensor Networks as a Data Structure in Probabilistic Modeling and for Learning Dynamical Laws from Data »
  Jens Eisert
• 2020 Workshop: First Workshop on Quantum Tensor Networks in Machine Learning »
  Xiao-Yang Liu · Qibin Zhao · Jacob Biamonte · Cesar F Caiafa · Paul Pu Liang · Nadav Cohen · Stefan Leichenauer
• 2020 : Opening Remarks »
  Xiao-Yang Liu
• 2020 Poster: Implicit Regularization in Deep Learning May Not Be Explainable by Norms »
  Noam Razin · Nadav Cohen
• 2020 Poster: Interpolation Technique to Speed Up Gradients Propagation in Neural ODEs »
  Talgat Daulbaev · Alexandr Katrutsa · Larisa Markeeva · Julia Gusak · Andrzej Cichocki · Ivan Oseledets
• 2019 : Coffee + Posters »
  Changhao Chen · Nils Gählert · Edouard Leurent · Johannes Lehner · Apratim Bhattacharyya · Harkirat Singh Behl · Teck Yian Lim · Shiho Kim · Jelena Novosel · Błażej Osiński · Arindam Das · Ruobing Shen · Jeffrey Hawke · Joachim Sicking · Babak Shahian Jahromi · Theja Tulabandhula · Claudio Michaelis · Evgenia Rusak · WENHANG BAO · Hazem Rashed · JP Chen · Amin Ansari · Jaekwang Cha · Mohamed Zahran · Daniele Reda · Jinhyuk Kim · Kim Dohyun · Ho Suk · Junekyo Jhung · Alexander Kister · Matthias Fahrland · Adam Jakubowski · Piotr Miłoś · Jean Mercat · Bruno Arsenali · Silviu Homoceanu · Xiao-Yang Liu · Philip Torr · Ahmad El Sallab · Ibrahim Sobh · Anurag Arnab · Krzysztof Galias
• 2019 Poster: Implicit Regularization in Deep Matrix Factorization »
  Sanjeev Arora · Nadav Cohen · Wei Hu · Yuping Luo
• 2019 Spotlight: Implicit Regularization in Deep Matrix Factorization »
  Sanjeev Arora · Nadav Cohen · Wei Hu · Yuping Luo
• 2019 Poster: Expressive power of tensor-network factorizations for probabilistic modeling »
  Ivan Glasser · Ryan Sweke · Nicola Pancotti · Jens Eisert · Ignacio Cirac
• 2018 : Poster Session »
  Sujay Sanghavi · Vatsal Shah · Yanyao Shen · Tianchen Zhao · Yuandong Tian · Tomer Galanti · Mufan Li · Gilad Cohen · Daniel Rothchild · Aristide Baratin · Devansh Arpit · Vagelis Papalexakis · Michael Perlmutter · Ashok Vardhan Makkuva · Pim de Haan · Yingyan Lin · Wanmo Kang · Cheolhyoung Lee · Hao Shen · Sho Yaida · Dan Roberts · Nadav Cohen · Philippe Casgrain · Dejiao Zhang · Tengyu Ma · Avinash Ravichandran · Julian Emilio Salazar · Bo Li · Davis Liang · Christopher Wong · Glen Bigan Mbeng · Animesh Garg
• 2018 : Posters and Open Discussions (see below for poster titles) »
  Ramya Malur Srinivasan · Miguel Perez · Yuanyuan Liu · Ben Wood · Dan Philps · Kyle Brown · Daniel Martin · Mykola Pechenizkiy · Luca Costabello · Rongguang Wang · Suproteem Sarkar · Sangwoong Yoon · Zhuoran Xiong · Enguerrand Horel · Zhu (Drew) Zhang · Ulf Johansson · Jonathan Kochems · Gregory Sidier · Prashant Reddy · Lana Cuthbertson · Yvonne Wambui · Christelle Marfaing · Galen Harrison · Irene Unceta Mendieta · Thomas Kehler · Mark Weber · Li Ling · Ceena Modarres · Abhinav Dhall · Arash Nourian · David Byrd · Ajay Chander · Xiao-Yang Liu · Hongyang Yang · Shuang (Sophie) Zhai · Freddy Lecue · Sirui Yao · Rory McGrath · Artur Garcez · Vangelis Bacoyannis · Alexandre Garcia · Lukas Gonon · Mark Ibrahim · Melissa Louie · Omid Ardakanian · Cecilia Sönströd · Kojin Oshiba · Chaofan Chen · Suchen Jin · aldo pareja · Toyo Suzumura
• 2018 Poster: Quadrature-based features for kernel approximation »
  Marina Munkhoeva · Yermek Kapushev · Evgeny Burnaev · Ivan Oseledets
• 2018 Spotlight: Quadrature-based features for kernel approximation »
  Marina Munkhoeva · Yermek Kapushev · Evgeny Burnaev · Ivan Oseledets
• 2017 Poster: Hierarchical Methods of Moments »
  Matteo Ruffini · Guillaume Rabusseau · Borja Balle
• 2017 Poster: Multitask Spectral Learning of Weighted Automata »
  Guillaume Rabusseau · Borja Balle · Joelle Pineau
• 2016 Poster: Low-Rank Regression with Tensor Responses »
  Guillaume Rabusseau · Hachem Kadri