Salakhutdinov, Ruslan

Reducing the dimensionality of data with neural networks

Hinton, G. E., & Salakhutdinov, R. R. (2006) · Science

Neural Networks and ApplicationsFace and Expression Recognition

Cited by 20,928

Show, Attend and Tell: Neural Image Caption Generation with Visual Attention

Xu, K., Ba, J., Kiros, R., Cho, K., Courville, A., Salakhutdinov, R., Zemel, R., & Bengio, Y. (2015) · arXiv

Multimodal Machine Learning ApplicationsVisual Attention and Saliency Detection

Cited by 8,248

XLNet: Generalized Autoregressive Pretraining for Language Understanding

Yang, Z., Dai, Z., Yang, Y., Carbonell, J., Salakhutdinov, R., & Le, Q. V. (2019) · arXiv

Topic ModelingNatural Language Processing Techniques

Cited by 6,687

Improving neural networks by preventing co-adaptation of feature detectors

Hinton, G. E., Srivastava, N., Krizhevsky, A., Sutskever, I., & Salakhutdinov, R. R. (2012) · arXiv

Neural Networks and ApplicationsAdvanced Neural Network Applications

Cited by 6,382

Transformer-XL: Attentive language models beyond a fixed-length context

Dai, Z., Yang, Z., Yang, Y., Carbonell, J., Le, Q., & Salakhutdinov, R. (2019) · Proceedings of the 57th Annual Meeting of the Association for Computational Linguistics

Topic ModelingNatural Language Processing Techniques

Cited by 3,169

HuBERT: Self-Supervised Speech Representation Learning by Masked Prediction of Hidden Units

Hsu, W.-N., Bolte, B., Tsai, Y.-H. H., Lakhotia, K., Salakhutdinov, R., & Mohamed, A. (2021) · IEEE/ACM Transactions on Audio, Speech, and Language Processing

Speech Recognition and SynthesisSpeech and Audio Processing

Cited by 2,983

Human-level concept learning through probabilistic program induction

Lake, B. M., Salakhutdinov, R., & Tenenbaum, J. B. (2015) · Science

Domain Adaptation and Few-Shot LearningBayesian Modeling and Causal Inference

Cited by 2,817

Aligning Books and Movies: Towards Story-Like Visual Explanations by Watching Movies and Reading Books

Zhu, Y., Kiros, R., Zemel, R., Salakhutdinov, R., Urtasun, R., Torralba, A., & Fidler, S. (2015) · 2015 IEEE International Conference on Computer Vision (ICCV)

Multimodal Machine Learning ApplicationsTopic Modeling

Cited by 2,264

Aligning Books and Movies: Towards Story-like Visual Explanations by Watching Movies and Reading Books

Zhu, Y., Kiros, R., Zemel, R., Salakhutdinov, R., Urtasun, R., Torralba, A., & Fidler, S. (2015) · arXiv

Multimodal Machine Learning ApplicationsTopic Modeling

Cited by 2,264

Multimodal Transformer for Unaligned Multimodal Language Sequences

Tsai, Y.-H. H., Bai, S., Liang, P. P., Kolter, J. Z., Morency, L.-P., & Salakhutdinov, R. (2019) · Proceedings of the 57th Annual Meeting of the Association for Computational Linguistics

Multimodal Machine Learning ApplicationsTime Series Analysis and Forecasting

Cited by 2,259

Restricted Boltzmann machines for collaborative filtering

Salakhutdinov, R., Mnih, A., & Hinton, G. (2007) · Proceedings of the 24th international conference on Machine learning

Recommender Systems and TechniquesNeural Networks and Applications

Cited by 1,885

Unsupervised Learning of Video Representations using LSTMs

Srivastava, N., Mansimov, E., & Salakhutdinov, R. (2015) · arXiv

Human Pose and Action RecognitionMultimodal Machine Learning Applications

Cited by 1,861

HotpotQA: A Dataset for Diverse, Explainable Multi-hop Question Answering

Yang, Z., Qi, P., Zhang, S., Bengio, Y., Cohen, W., Salakhutdinov, R., & Manning, C. D. (2018) · Proceedings of the 2018 Conference on Empirical Methods in Natural Language Processing

Topic ModelingMultimodal Machine Learning Applications

Cited by 1,804

Skip-Thought Vectors

Kiros, R., Zhu, Y., Salakhutdinov, R., Zemel, R. S., Torralba, A., Urtasun, R., & Fidler, S. (2015) · arXiv

Topic ModelingSentiment Analysis and Opinion Mining

Cited by 1,293

Semantic hashing

Salakhutdinov, R., & Hinton, G. (2009) · International Journal of Approximate Reasoning

Topic ModelingAdvanced Image and Video Retrieval Techniques

Cited by 1,246

Importance Weighted Autoencoders

Burda, Y., Grosse, R., & Salakhutdinov, R. (2015) · arXiv

Gaussian Processes and Bayesian InferenceTopic Modeling

Cited by 644

Beyond the Imitation Game: Quantifying and extrapolating the capabilities of language models

Srivastava, A., Rastogi, A., Rao, A., Shoeb, A. A. M., Abid, A., Fisch, A., Brown, A. R., Santoro, A., Gupta, A., Garriga-Alonso, A., et al. (2022) · arXiv

Topic ModelingNatural Language Processing Techniques

Cited by 569

On the quantitative analysis of deep belief networks

Salakhutdinov, R., & Murray, I. (2008) · Proceedings of the 25th international conference on Machine learning - ICML '08

Neural Networks and ApplicationsBayesian Modeling and Causal Inference

Cited by 411

Gated-Attention Readers for Text Comprehension

Dhingra, B., Liu, H., Yang, Z., Cohen, W., & Salakhutdinov, R. (2017) · Proceedings of the 55th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)

Topic ModelingInformation Retrieval and Search Behavior

Cited by 366

Style transfer through back-translation

Prabhumoye, S., Tsvetkov, Y., Salakhutdinov, R., & Black, A. W. (2018) · Proceedings of the 56th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)

Generative Adversarial Networks and Image SynthesisAuthorship Attribution and Profiling

Cited by 348

Learning Factorized Multimodal Representations

Tsai, Y.-H. H., Liang, P. P., Zadeh, A., Morency, L.-P., & Salakhutdinov, R. (2018) · arXiv

Multimodal Machine Learning ApplicationsSentiment Analysis and Opinion Mining

Cited by 323

Learning to explore using active neural SLAM

Chaplot, D. S., Gandhi, D., Gupta, S., Gupta, A., & Salakhutdinov, R. (2020) · arXiv

Reinforcement Learning in RoboticsRobotics and Sensor-Based Localization

Cited by 318

Neural Topological SLAM for Visual Navigation

Singh Chaplot, D., Salakhutdinov, R., Gupta, A., & Gupta, S. (2020) · 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)

Robotics and Sensor-Based LocalizationReinforcement Learning in Robotics

Cited by 241

Neural Map: Structured Memory for Deep Reinforcement Learning

Parisotto, E., & Salakhutdinov, R. (2017) · arXiv

Reinforcement Learning in RoboticsArtificial Intelligence in Games

Cited by 178