Poster "transfer learning" Papers
51 papers found • Page 1 of 2
Conference
Accessing Vision Foundation Models via ImageNet-1K
Yitian Zhang, Xu Ma, Yue Bai et al.
A Decade's Battle on Dataset Bias: Are We There Yet?
Zhuang Liu, Kaiming He
Adversarial Robustness of Discriminative Self-Supervised Learning in Vision
Ömer Veysel Çağatan, Ömer TAL, M. Emre Gursoy
A Stochastic Approach to the Subset Selection Problem via Mirror Descent
Dan Greenstein, Elazar Gershuni, Ilan Ben-Bassat et al.
BoltzNCE: Learning likelihoods for Boltzmann Generation with Stochastic Interpolants and Noise Contrastive Estimation
Rishal Aggarwal, Jacky Chen, Nicholas Boffi et al.
Building, Reusing, and Generalizing Abstract Representations from Concrete Sequences
Shuchen Wu, Mirko Thalmann, Peter Dayan et al.
Diffusion-based Neural Network Weights Generation
Bedionita Soro, Bruno Andreis, Hayeon Lee et al.
Generative Graph Pattern Machine
Zehong Wang, Zheyuan Zhang, Tianyi Ma et al.
Geometry-Aware Collaborative Multi-Solutions Optimizer for Model Fine-Tuning with Parameter Efficiency
Van-Anh Nguyen, Trung Le, Mehrtash Harandi et al.
GOAL: A Generalist Combinatorial Optimization Agent Learner
Darko Drakulić, Sofia Michel, Jean-Marc Andreoli
Implicit In-context Learning
Zhuowei Li, Zihao Xu, Ligong Han et al.
Learning Interpretable Hierarchical Dynamical Systems Models from Time Series Data
Manuel Brenner, Elias Weber, Georgia Koppe et al.
Learning Skill-Attributes for Transferable Assessment in Video
Kumar Ashutosh, Kristen Grauman
Mamba-Adaptor: State Space Model Adaptor for Visual Recognition
Fei Xie, Jiahao Nie, Yujin Tang et al.
Morphing Tokens Draw Strong Masked Image Models
Taekyung Kim, Byeongho Heo, Dongyoon Han
On the Generalization of Handwritten Text Recognition Models
Carlos Garrido-Munoz, Jorge Calvo-Zaragoza
Optimal Learning of Kernel Logistic Regression for Complex Classification Scenarios
Hongwei Wen, Annika Betken, Hanyuan Hang
Optimization with Access to Auxiliary Information
EL MAHDI CHAYTI, Sai Karimireddy
Parameter Efficient Mamba Tuning via Projector-targeted Diagonal-centric Linear Transformation
Seokil Ham, Hee-Seon Kim, Sangmin Woo et al.
Provable Sample-Efficient Transfer Learning Conditional Diffusion Models via Representation Learning
Ziheng Cheng, Tianyu Xie, Shiyue Zhang et al.
Rethinking Hebbian Principle: Low-Dimensional Structural Projection for Unsupervised Learning
Shikuang Deng, Jiayuan Zhang, Yuhang Wu et al.
Robust Transfer Learning with Unreliable Source Data
Jianqing Fan, Cheng Gao, Jason Klusowski
SciVid: Cross-Domain Evaluation of Video Models in Scientific Applications
Yana Hasson, Pauline Luc, Liliane Momeni et al.
The Catechol Benchmark: Time-series Solvent Selection Data for Few-shot Machine Learning
Toby Boyne, Juan Campos, Rebecca Langdon et al.
TransiT: Transient Transformer for Non-line-of-sight Videography
Ruiqian Li, Siyuan Shen, Suan Xia et al.
${\rm E}(3)$-Equivariant Actor-Critic Methods for Cooperative Multi-Agent Reinforcement Learning
Dingyang Chen, Qi Zhang
CARTE: Pretraining and Transfer for Tabular Learning
Myung Jun Kim, Leo Grinsztajn, Gael Varoquaux
DNA-SE: Towards Deep Neural-Nets Assisted Semiparametric Estimation
Qinshuo Liu, Zixin Wang, Xi'an Li et al.
Encodings for Prediction-based Neural Architecture Search
Yash Akhauri, Mohamed Abdelfattah
Event Camera Data Dense Pre-training
Yan Yang, Liyuan Pan, Liu liu
Feature Reuse and Scaling: Understanding Transfer Learning with Protein Language Models
Francesca-Zhoufan Li, Ava Amini, Yisong Yue et al.
Forget Sharpness: Perturbed Forgetting of Model Biases Within SAM Dynamics
Ankit Vani, Frederick Tung, Gabriel Oliveira et al.
Graph Positional and Structural Encoder
Semih Cantürk, Renming Liu, Olivier Lapointe-Gagné et al.
Guarantees for Nonlinear Representation Learning: Non-identical Covariates, Dependent Data, Fewer Samples
Thomas T. Zhang, Bruce Lee, Ingvar Ziemann et al.
Is Inverse Reinforcement Learning Harder than Standard Reinforcement Learning? A Theoretical Perspective
Lei Zhao, Mengdi Wang, Yu Bai
Learning from Memory: Non-Parametric Memory Augmented Self-Supervised Learning of Visual Features
Thalles Silva, Helio Pedrini, Adín Ramírez Rivera
Matrix Information Theory for Self-Supervised Learning
Yifan Zhang, Zhiquan Tan, Jingqin Yang et al.
MF-CLR: Multi-Frequency Contrastive Learning Representation for Time Series
Jufang Duan, Wei Zheng, Yangzhou Du et al.
Minimum-Norm Interpolation Under Covariate Shift
Neil Mallinar, Austin Zane, Spencer Frei et al.
Non-transferable Pruning
Ruyi Ding, Lili Su, A. Adam Ding et al.
NVS-Adapter: Plug-and-Play Novel View Synthesis from a Single Image
Yoonwoo Jeong, Jinwoo Lee, Chiheon Kim et al.
On Hypothesis Transfer Learning of Functional Linear Models
Haotian Lin, Matthew Reimherr
Position: Considerations for Differentially Private Learning with Large-Scale Public Pretraining
Florian Tramer, Gautam Kamath, Nicholas Carlini
Position: Will we run out of data? Limits of LLM scaling based on human-generated data
Pablo Villalobos, Anson Ho, Jaime Sevilla et al.
R^2-Tuning: Efficient Image-to-Video Transfer Learning for Video Temporal Grounding
Ye Liu, Jixuan He, Wanhua Li et al.
To Supervise or Not to Supervise: Understanding and Addressing the Key Challenges of Point Cloud Transfer Learning
Souhail Hadgi, Lei Li, Maks Ovsjanikov
Training Like a Medical Resident: Context-Prior Learning Toward Universal Medical Image Segmentation
Yunhe Gao
Triplet Interaction Improves Graph Transformers: Accurate Molecular Graph Learning with Triplet Graph Transformers
Md Shamim Hussain, Mohammed Zaki, Dharmashankar Subramanian
Unleashing the Power of Meta-tuning for Few-shot Generalization Through Sparse Interpolated Experts
Shengzhuang Chen, Jihoon Tack, Yunqiao Yang et al.
ViC-MAE: Self-Supervised Representation Learning from Images and Video with Contrastive Masked Autoencoders
Jefferson Hernandez, Ruben Villegas, Vicente Ordonez