default search action
Google
Google Scholar
Semantic Scholar
Internet Archive Scholar
CiteSeerX
ORCIDDevansh Arpit
Person information
Refine list
refinements active!
zoomed in on ?? of ?? records
view refined list in
export refined list as
2020 – today
- 2024
[c22]Itai Feigenbaum, Devansh Arpit, Shelby Heinecke, Juan Carlos Niebles, Weiran Yao, Caiming Xiong, Silvio Savarese, Huan Wang:
Causal Layering via Conditional Entropy. CLeaR 2024: 1176-1191- [c21]Weiran Yao, Shelby Heinecke, Juan Carlos Niebles, Zhiwei Liu, Yihao Feng, Le Xue, Rithesh R. N., Zeyuan Chen, Jianguo Zhang, Devansh Arpit, Ran Xu, Phil Mui, Huan Wang, Caiming Xiong, Silvio Savarese:
Retroformer: Retrospective Large Language Agents with Policy Gradient Optimization. ICLR 2024 - [i30]Itai Feigenbaum, Devansh Arpit, Huan Wang, Shelby Heinecke, Juan Carlos Niebles, Weiran Yao, Caiming Xiong, Silvio Savarese:
Editing Arbitrary Propositions in LLMs without Subject Labels. CoRR abs/2401.07526 (2024) - [i29]Itai Feigenbaum, Devansh Arpit, Huan Wang, Shelby Heinecke, Juan Carlos Niebles, Weiran Yao, Caiming Xiong, Silvio Savarese:
Causal Layering via Conditional Entropy. CoRR abs/2401.10495 (2024) - 2023
- [j1]Aadyot Bhatnagar, Paul Kassianik, Chenghao Liu, Tian Lan, Wenzhuo Yang, Rowan Cassius, Doyen Sahoo, Devansh Arpit, Sri Subramanian, Gerald Woo, Amrita Saha, Arun Kumar Jagota, Gokulakrishnan Gopalakrishnan, Manpreet Singh, K. C. Krithika, Sukumar Maddineni, Dae-ki Cho, Bo Zong, Yingbo Zhou, Caiming Xiong, Silvio Savarese, Steven C. H. Hoi, Huan Wang:
Merlion: End-to-End Machine Learning for Time Series. J. Mach. Learn. Res. 24: 226:1-226:6 (2023) - [i28]Devansh Arpit, Matthew Fernandez, Chenghao Liu, Weiran Yao, Wenzhuo Yang, Paul Josel, Shelby Heinecke
, Eric Hu, Huan Wang, Stephen C. H. Hoi, Caiming Xiong, Kun Zhang, Juan Carlos Niebles:
Salesforce CausalAI Library: A Fast and Scalable Framework for Causal Analysis of Time Series and Tabular Data. CoRR abs/2301.10859 (2023) - [i27]Itai Feigenbaum, Huan Wang, Shelby Heinecke, Juan Carlos Niebles, Weiran Yao, Caiming Xiong, Devansh Arpit:
On the Unlikelihood of D-Separation. CoRR abs/2303.05628 (2023) - [i26]Rithesh Murthy, Shelby Heinecke, Juan Carlos Niebles, Zhiwei Liu, Le Xue, Weiran Yao, Yihao Feng, Zeyuan Chen, Akash Gokul, Devansh Arpit, Ran Xu, Phil Mui, Huan Wang, Caiming Xiong, Silvio Savarese:
REX: Rapid Exploration and eXploitation for AI Agents. CoRR abs/2307.08962 (2023) - [i25]Weiran Yao, Shelby Heinecke, Juan Carlos Niebles, Zhiwei Liu, Yihao Feng, Le Xue, Rithesh Murthy, Zeyuan Chen, Jianguo Zhang, Devansh Arpit, Ran Xu, Phil Mui, Huan Wang, Caiming Xiong, Silvio Savarese:
Retroformer: Retrospective Large Language Agents with Policy Gradient Optimization. CoRR abs/2308.02151 (2023) - [i24]Zhiwei Liu, Weiran Yao, Jianguo Zhang, Le Xue, Shelby Heinecke, Rithesh Murthy, Yihao Feng, Zeyuan Chen, Juan Carlos Niebles, Devansh Arpit, Ran Xu, Phil Mui, Huan Wang, Caiming Xiong, Silvio Savarese:
BOLAA: Benchmarking and Orchestrating LLM-augmented Autonomous Agents. CoRR abs/2308.05960 (2023) - 2022
- [c20]Devansh Arpit, Huan Wang, Yingbo Zhou, Caiming Xiong:
Ensemble of Averages: Improving Model Selection and Boosting Performance in Domain Generalization. NeurIPS 2022 - 2021
- [c19]Stanislaw Jastrzebski, Devansh Arpit, Oliver Åstrand, Giancarlo Kerg, Huan Wang, Caiming Xiong, Richard Socher, Kyunghyun Cho, Krzysztof J. Geras:
Catastrophic Fisher Explosion: Early Phase Fisher Matrix Impacts Generalization. ICML 2021: 4772-4784 - [i23]Aadyot Bhatnagar, Paul Kassianik, Chenghao Liu, Tian Lan, Wenzhuo Yang, Rowan Cassius, Doyen Sahoo, Devansh Arpit, Sri Subramanian, Gerald Woo, Amrita Saha, Arun Kumar Jagota, Gokulakrishnan Gopalakrishnan, Manpreet Singh, K. C. Krithika, Sukumar Maddineni, Dae-ki Cho, Bo Zong, Yingbo Zhou, Caiming Xiong, Silvio Savarese, Steven C. H. Hoi, Huan Wang:
Merlion: A Machine Learning Library for Time Series. CoRR abs/2109.09265 (2021) - [i22]Bram Wallace, Devansh Arpit, Huan Wang, Caiming Xiong:
Learning Rich Nearest Neighbor Representations from Self-supervised Ensembles. CoRR abs/2110.10293 (2021) - [i21]Devansh Arpit, Aadyot Bhatnagar, Huan Wang, Caiming Xiong:
Momentum Contrastive Autoencoder: Using Contrastive Learning for Latent Space Distribution Matching in WAE. CoRR abs/2110.10303 (2021) - [i20]Devansh Arpit, Huan Wang, Yingbo Zhou, Caiming Xiong:
Ensemble of Averages: Improving Model Selection and Boosting Performance in Domain Generalization. CoRR abs/2110.10832 (2021) - 2020
- [c18]Stanislaw Jastrzebski, Maciej Szymczak, Stanislav Fort, Devansh Arpit, Jacek Tabor, Kyunghyun Cho, Krzysztof J. Geras:
The Break-Even Point on Optimization Trajectories of Deep Neural Networks. ICLR 2020 - [i19]Devansh Arpit, Huan Wang, Caiming Xiong, Richard Socher, Yoshua Bengio:
Neural Bayes: A Generic Parameterization Method for Unsupervised Representation Learning. CoRR abs/2002.09046 (2020) - [i18]Stanislaw Jastrzebski, Maciej Szymczak, Stanislav Fort, Devansh Arpit, Jacek Tabor, Kyunghyun Cho, Krzysztof J. Geras:
The Break-Even Point on Optimization Trajectories of Deep Neural Networks. CoRR abs/2002.09572 (2020) - [i17]Stanislaw Jastrzebski, Devansh Arpit, Oliver Åstrand, Giancarlo Kerg, Huan Wang, Caiming Xiong, Richard Socher, Kyunghyun Cho, Krzysztof J. Geras:
Catastrophic Fisher Explosion: Early Phase Fisher Matrix Impacts Generalization. CoRR abs/2012.14193 (2020)
2010 – 2019
- 2019
- [c17]Bhargav Kanuparthi, Devansh Arpit, Giancarlo Kerg, Nan Rosemary Ke, Ioannis Mitliagkas, Yoshua Bengio:
h-detach: Modifying the LSTM Gradient Towards Better Optimization. ICLR (Poster) 2019 - [c16]Nasim Rahaman, Aristide Baratin, Devansh Arpit, Felix Draxler, Min Lin, Fred A. Hamprecht, Yoshua Bengio, Aaron C. Courville:
On the Spectral Bias of Neural Networks. ICML 2019: 5301-5310 - [c15]Devansh Arpit, Víctor Campos, Yoshua Bengio:
How to Initialize your Network? Robust Initialization for WeightNorm & ResNets. NeurIPS 2019: 10900-10909 - [i16]Devansh Arpit, Yoshua Bengio:
The Benefits of Over-parameterization at Initialization in Deep ReLU Networks. CoRR abs/1901.03611 (2019) - [i15]Devansh Arpit, Victor Campos, Yoshua Bengio:
How to Initialize your Network? Robust Initialization for WeightNorm & ResNets. CoRR abs/1906.02341 (2019) - [i14]Devansh Arpit, Caiming Xiong, Richard Socher:
Entropy Penalty: Towards Generalization Beyond the IID Assumption. CoRR abs/1910.00164 (2019) - 2018
- [c14]Stanislaw Jastrzebski, Zachary Kenton, Devansh Arpit, Nicolas Ballas, Asja Fischer, Yoshua Bengio, Amos J. Storkey:
Width of Minima Reached by Stochastic Gradient Descent is Influenced by Learning Rate to Batch Size Ratio. ICANN (3) 2018: 392-402 - [c13]Stanislaw Jastrzebski, Devansh Arpit, Nicolas Ballas, Vikas Verma, Tong Che, Yoshua Bengio:
Residual Connections Encourage Iterative Inference. ICLR (Poster) 2018 - [c12]Stanislaw Jastrzebski, Zachary Kenton, Devansh Arpit, Nicolas Ballas, Asja Fischer, Yoshua Bengio, Amos J. Storkey:
Finding Flatter Minima with SGD. ICLR (Workshop) 2018 - [c11]Konrad Zolna, Devansh Arpit, Dendi Suhubdy, Yoshua Bengio:
Fraternal Dropout. ICLR (Poster) 2018 - [i13]Chen Xing, Devansh Arpit, Christos Tsirigotis, Yoshua Bengio:
A Walk with SGD. CoRR abs/1802.08770 (2018) - [i12]Nasim Rahaman, Devansh Arpit, Aristide Baratin, Felix Draxler, Min Lin, Fred A. Hamprecht, Yoshua Bengio, Aaron C. Courville:
On the Spectral Bias of Deep Neural Networks. CoRR abs/1806.08734 (2018) - [i11]Devansh Arpit, Bhargav Kanuparthi, Giancarlo Kerg, Nan Rosemary Ke, Ioannis Mitliagkas, Yoshua Bengio:
h-detach: Modifying the LSTM Gradient Towards Better Optimization. CoRR abs/1810.03023 (2018) - 2017
- [c10]Neeti Narayan, Nishant Sankaran, Devansh Arpit, Karthik Dantu, Srirangaraj Setlur, Venu Govindaraju:
Person Re-identification for Improved Multi-person Multi-camera Tracking by Continuous Entity Association. CVPR Workshops 2017: 566-572 - [c9]David Krueger, Nicolas Ballas, Stanislaw Jastrzebski, Devansh Arpit, Maxinder S. Kanwal, Tegan Maharaj, Emmanuel Bengio, Asja Fischer, Aaron C. Courville:
Deep Nets Don't Learn via Memorization. ICLR (Workshop) 2017 - [c8]Devansh Arpit, Stanislaw Jastrzebski, Nicolas Ballas, David Krueger, Emmanuel Bengio, Maxinder S. Kanwal, Tegan Maharaj, Asja Fischer, Aaron C. Courville, Yoshua Bengio, Simon Lacoste-Julien:
A Closer Look at Memorization in Deep Networks. ICML 2017: 233-242 - [i10]Devansh Arpit, Stanislaw Jastrzebski, Nicolas Ballas, David Krueger, Emmanuel Bengio, Maxinder S. Kanwal, Tegan Maharaj, Asja Fischer, Aaron C. Courville, Yoshua Bengio, Simon Lacoste-Julien:
A Closer Look at Memorization in Deep Networks. CoRR abs/1706.05394 (2017) - [i9]Stanislaw Jastrzebski, Devansh Arpit, Nicolas Ballas, Vikas Verma, Tong Che, Yoshua Bengio:
Residual Connections Encourage Iterative Inference. CoRR abs/1710.04773 (2017) - [i8]Konrad Zolna, Devansh Arpit, Dendi Suhubdy, Yoshua Bengio:
Fraternal Dropout. CoRR abs/1711.00066 (2017) - [i7]Stanislaw Jastrzebski, Zachary Kenton, Devansh Arpit, Nicolas Ballas, Asja Fischer, Yoshua Bengio, Amos J. Storkey:
Three Factors Influencing Minima in SGD. CoRR abs/1711.04623 (2017) - [i6]Samira Shabanian, Devansh Arpit, Adam Trischler, Yoshua Bengio:
Variational Bi-LSTMs. CoRR abs/1711.05717 (2017) - 2016
- [c7]Devansh Arpit, Chetan Ramaiah, Venu Govindaraju:
Subspace learning via low rank projections for dimensionality reduction. BTAS 2016: 1-7 - [c6]Devansh Arpit, Yingbo Zhou, Hung Q. Ngo, Venu Govindaraju:
Why Regularized Auto-Encoders learn Sparse Representation? ICML 2016: 136-144 - [c5]Devansh Arpit, Yingbo Zhou, Bhargava Urala Kota, Venu Govindaraju:
Normalization Propagation: A Parametric Technique for Removing Internal Covariate Shift in Deep Networks. ICML 2016: 1168-1176 - [i5]Devansh Arpit, Yingbo Zhou, Bhargava Urala Kota, Venu Govindaraju:
Normalization Propagation: A Parametric Technique for Removing Internal Covariate Shift in Deep Networks. CoRR abs/1603.01431 (2016) - [i4]Devansh Arpit, Hung Q. Ngo, Yingbo Zhou, Nils Napp, Venu Govindaraju:
Towards Optimality Conditions for Non-Linear Networks. CoRR abs/1605.07145 (2016) - 2015
- [i3]Devansh Arpit, Yingbo Zhou, Hung Q. Ngo, Venu Govindaraju:
Why Regularized Auto-Encoders learn Sparse Representation? CoRR abs/1505.05561 (2015) - 2014
- [c4]Devansh Arpit, Ifeoma Nwogu, Venu Govindaraju:
Dimensionality Reduction with Subspace Structure Preservation. NIPS 2014: 712-720 - [i2]Devansh Arpit, Gaurav Srivastava, Venu Govindaraju:
Randomized Subspace Learning Algorithms with Subspace Structure Preservation Guarantees. CoRR abs/1401.4489 (2014) - [i1]Devansh Arpit, Ifeoma Nwogu, Venu Govindaraju:
Dimensionality Reduction with Subspace Structure Preservation. CoRR abs/1412.2404 (2014) - 2013
- [c3]Devansh Arpit, Shuang Wu, Pradeep Natarajan, Rohit Prasad, Premkumar Natarajan:
Ridge Regression based classifiers for large scale class imbalanced datasets. WACV 2013: 267-274 - 2012
- [c2]Devansh Arpit, Gaurav Srivastava, Yun Fu:
Locality-constrained Low Rank Coding for face recognition. ICPR 2012: 1687-1690 - 2011
- [c1]Devansh Arpit, Anoop M. Namboodiri:
Fingerprint feature extraction from gray scale images by ridge tracing. IJCB 2011: 1-8
Coauthor Index
manage site settings
To protect your privacy, all features that rely on external API calls from your browser are turned off by default. You need to opt-in for them to become active. All settings here will be stored as cookies with your web browser. For more information see our F.A.Q.
Unpaywalled article links
Add open access links from 
to the list of external document links (if available).
Privacy notice: By enabling the option above, your browser will contact the API of unpaywall.org to load hyperlinks to open access articles. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the Unpaywall privacy policy.
Archived links via Wayback Machine
For web page which are no longer available, try to retrieve content from the 
of the Internet Archive (if available).
Privacy notice: By enabling the option above, your browser will contact the API of archive.org to check for archived content of web pages that are no longer available. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the Internet Archive privacy policy.
Reference lists
Add a list of references from 
, 
, and 
to record detail pages.
load references from crossref.org and opencitations.net
Privacy notice: By enabling the option above, your browser will contact the APIs of crossref.org, opencitations.net, and semanticscholar.org to load article reference information. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the Crossref privacy policy and the OpenCitations privacy policy, as well as the AI2 Privacy Policy covering Semantic Scholar.
Citation data
Add a list of citing articles from and to record detail pages.
load citations from opencitations.net
Privacy notice: By enabling the option above, your browser will contact the API of opencitations.net and semanticscholar.org to load citation information. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the OpenCitations privacy policy as well as the AI2 Privacy Policy covering Semantic Scholar.
OpenAlex data
Load additional information about publications from 
.
Privacy notice: By enabling the option above, your browser will contact the API of openalex.org to load additional information. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the information given by OpenAlex.
last updated on 2024-12-13 20:04 CET by the dblp team
all metadata released as open data under CC0 1.0 license
see also: Terms of Use | Privacy Policy | Imprint
dblp was originally created in 1993 at:
since 2018, dblp has been operated and maintained by:
the dblp computer science bibliography is funded and supported by:
