NeurIPS 2023 Workshop WANT Submissions

Accelerating Deep Learning using Ivy
Guillermo Sanchez-Brizuela, Ved Patwardhan, Matthew Barrett, Paul Anderson, Mustafa Hani, Daniel James Lenton
- Published: 28 Oct 2023, Last Modified: 01 Dec 2023
- WANT@NeurIPS 2023 Poster
- Readers: Everyone
Remaining-Useful-Life Prediction and Uncertainty Quantification using LSTM Ensembles for Aircraft Engines
Oishi Deb, Emmanouil Benetos, Philip Torr
- Published: 28 Oct 2023, Last Modified: 05 Dec 2023
- WANT@NeurIPS 2023 Poster
- Readers: Everyone
LeanFlex-GKP: Advancing Hassle-Free Structured Pruning with Simple Flexible Group Count
Jiamu Zhang, Shaochen Zhong, Andrew Ye, Zirui Liu, Kaixiong Zhou, Xia Hu, Shuai Xu, Vipin Chaudhary
- Published: 28 Oct 2023, Last Modified: 01 Dec 2023
- WANT@NeurIPS 2023 Poster
- Readers: Everyone
Task Arithmetic with LoRA for Continual Learning
Rajas Chitale, Ankit Vaidya, Aditya Kane, Archana Santosh Ghotkar
- Published: 28 Oct 2023, Last Modified: 23 Nov 2023
- WANT@NeurIPS 2023 Poster
- Readers: Everyone
A Quadratic Synchronization Rule for Distributed Deep Learning
Xinran Gu, Kaifeng Lyu, Sanjeev Arora, Jingzhao Zhang, Longbo Huang
- Published: 28 Oct 2023, Last Modified: 01 Dec 2023
- WANT@NeurIPS 2023 Poster
- Readers: Everyone
InstaTune: Instantaneous Neural Architecture Search During Fine-Tuning
Sharath Nittur Sridhar, Souvik Kundu, Sairam Sundaresan, Maciej Szankin, Anthony Sarah
- Published: 28 Oct 2023, Last Modified: 01 Dec 2023
- WANT@NeurIPS 2023 Poster
- Readers: Everyone
Efficient and Approximate Per-Example Gradient Norms for Gradient Noise Scale
Gavia Gray, Anshul Samar, Joel Hestness
- Published: 28 Oct 2023, Last Modified: 30 Nov 2023
- WANT@NeurIPS 2023 Poster
- Readers: Everyone
Bandit-Driven Batch Selection for Robust Learning under Label Noise
Michal Lisicki, Graham W. Taylor, Mihai Nica
- Published: 28 Oct 2023, Last Modified: 01 Dec 2023
- WANT@NeurIPS 2023 Poster
- Readers: Everyone
Patch Gradient Descent: Training Neural Networks on Very Large Images
Deepak Gupta, Gowreesh Mago, Arnav Chavan, Dilip Prasad, Rajat Mani Thomas
- Published: 28 Oct 2023, Last Modified: 28 Oct 2023
- WANT@NeurIPS 2023 Poster
- Readers: Everyone
CoTFormer: More Tokens With Attention Make Up For Less Depth
Amirkeivan Mohtashami, Matteo Pagliardini, Martin Jaggi
- Published: 28 Oct 2023, Last Modified: 29 Nov 2023
- WANT@NeurIPS 2023 Oral
- Readers: Everyone
Sparse Iso-FLOP Transformations for Maximizing Training Efficiency
Vithursan Thangarasa, Shreyas Saxena, Abhay Gupta, Sean Lie
- Published: 28 Oct 2023, Last Modified: 01 Dec 2023
- WANT@NeurIPS 2023 Poster
- Readers: Everyone
Tiny Graph Convolutional Networks with Topologically Consistent Magnitude Pruning
Hichem Sahbi
- Published: 28 Oct 2023, Last Modified: 30 Nov 2023
- WANT@NeurIPS 2023 Poster
- Readers: Everyone
DAREL: Data Reduction with Losses for Training Acceleration of Real and Hypercomplex Neural Networks
Alexander Vladimirovich Demidovskij, Aleksei Trutnev, Artem Tugarev, Igor Salnikov, Stanislav Pavlov
- Published: 28 Oct 2023, Last Modified: 01 Dec 2023
- WANT@NeurIPS 2023 Poster
- Readers: Everyone
DYAD: A Descriptive Yet Abjuring Density efficient approximation to linear neural network layers
Sarin Eapen Chandy, Varun Prashant Gangal, Yi Yang, Gabriel Maggiotti
- Published: 28 Oct 2023, Last Modified: 01 Dec 2023
- WANT@NeurIPS 2023 Poster
- Readers: Everyone
Efficient Parallelization Layouts for Large-Scale Distributed Model Training
Johannes Hagemann, Samuel Weinbach, Konstantin Dobler, Maximilian Schall, Gerard de Melo
- Published: 28 Oct 2023, Last Modified: 30 Nov 2023
- WANT@NeurIPS 2023 Oral
- Readers: Everyone
Something for (almost) nothing: improving deep ensemble calibration using unlabeled data
Konstantinos Pitas, Julyan Arbel
- Published: 28 Oct 2023, Last Modified: 01 Dec 2023
- WANT@NeurIPS 2023 Poster
- Readers: Everyone
DONUT-hole: DONUT Sparsification by Harnessing Knowledge and Optimizing Learning Efficiency
Azhar Shaikh, Michael Cochez, Denis Diachkov, Michiel de Rijcke, Sahar Yousefi
- Published: 28 Oct 2023, Last Modified: 17 Nov 2023
- WANT@NeurIPS 2023 Poster
- Readers: Everyone
Improving Deep Ensembles without Communication
Konstantinos Pitas, Michael Arbel, Julyan Arbel
- Published: 28 Oct 2023, Last Modified: 01 Dec 2023
- WANT@NeurIPS 2023 Poster
- Readers: Everyone
Batched Low-Rank Adaptation of Foundation Models
Yeming Wen, Swarat Chaudhuri
- Published: 28 Oct 2023, Last Modified: 29 Nov 2023
- WANT@NeurIPS 2023 Poster
- Readers: Everyone
Embarrassingly Simple Dataset Distillation
Yunzhen Feng, Shanmukha Ramakrishna Vedantam, Julia Kempe
- Published: 28 Oct 2023, Last Modified: 30 Nov 2023
- WANT@NeurIPS 2023 Poster
- Readers: Everyone
Local LoRA: Memory-Efficient Fine-Tuning of Large Language Models
Oscar Key, Jean Kaddour, Pasquale Minervini
- Published: 28 Oct 2023, Last Modified: 01 Dec 2023
- WANT@NeurIPS 2023 Poster
- Readers: Everyone
Dynamic Observation Policies in Observation Cost-Sensitive Reinforcement Learning
Colin Bellinger, Mark Crowley, Isaac Tamblyn
- Published: 28 Oct 2023, Last Modified: 28 Oct 2023
- WANT@NeurIPS 2023 Poster
- Readers: Everyone
Cooperative Learning for Cost-Adaptive Inference
Xingli Fang, Richard M Bradford, Jung-Eun Kim
- Published: 28 Oct 2023, Last Modified: 29 Nov 2023
- WANT@NeurIPS 2023 Poster
- Readers: Everyone
Early Weight Averaging meets High Learning Rates for LLM Pre-training
Sunny Sanyal, Atula Tejaswi Neerkaje, Jean Kaddour, Abhishek Kumar, sujay sanghavi
- Published: 28 Oct 2023, Last Modified: 30 Nov 2023
- WANT@NeurIPS 2023 Poster
- Readers: Everyone
A foundation for exact binarized morphological neural networks
Theodore Aouad, Hugues Talbot
- Published: 28 Oct 2023, Last Modified: 30 Nov 2023
- WANT@NeurIPS 2023 Poster
- Readers: Everyone