ICLR Papers
6,124 papers found • Page 92 of 123
FasterViT: Fast Vision Transformers with Hierarchical Attention
Ali Hatamizadeh, Greg Heinrich, Hongxu Yin et al.
Fast, Expressive $\mathrm{SE}(n)$ Equivariant Networks through Weight-Sharing in Position-Orientation Space
Erik Bekkers, Sharvaree Vadgama, Rob Hesselink et al.
Fast Hyperboloid Decision Tree Algorithms
Philippe Chlenski, Ethan Turok, Antonio Moretti et al.
Fast Imitation via Behavior Foundation Models
Matteo Pirotta, Andrea Tirinzoni, Ahmed Touati et al.
Fast Updating Truncated SVD for Representation Learning with Sparse Matrices
Haoran Deng, Yang Yang, Jiahe Li et al.
Fast Value Tracking for Deep Reinforcement Learning
Frank Shih, Faming Liang
FeatUp: A Model-Agnostic Framework for Features at Any Resolution
Stephanie Fu, Mark Hamilton, Laura E. Brandt et al.
Feature-aligned N-BEATS with Sinkhorn divergence
Joonhun Lee, Myeongho Jeon, Myungjoo Kang et al.
Feature Collapse
Thomas Laurent, James von Brecht, Xavier Bresson
Feature emergence via margin maximization: case studies in algebraic tasks
Depen Morwani, Benjamin Edelman, Costin-Andrei Oncescu et al.
FedCDA: Federated Learning with Cross-rounds Divergence-aware Aggregation
Haozhao Wang, Haoran Xu, Yichen Li et al.
FedCompass: Efficient Cross-Silo Federated Learning on Heterogeneous Client Devices Using a Computing Power-Aware Scheduler
Zilinghan Li, Pranshu Chaturvedi, Shilan He et al.
FedDA: Faster Adaptive Gradient Methods for Federated Constrained Optimization
Junyi Li, Feihu Huang, Heng Huang
Federated Causal Discovery from Heterogeneous Data
Loka Li, Ignavier Ng, Gongxu Luo et al.
Federated Orthogonal Training: Mitigating Global Catastrophic Forgetting in Continual Federated Learning
Yavuz Faruk Bakman, Duygu Nur Yaldiz, Yahya Ezzeldin et al.
Federated Q-Learning: Linear Regret Speedup with Low Communication Cost
Zhong Zheng, Fengyu Gao, Lingzhou Xue et al.
Federated Recommendation with Additive Personalization
Zhiwei Li, Guodong Long, Tianyi Zhou
Federated Text-driven Prompt Generation for Vision-Language Models
Chen Qiu, Xingyu Li, Chaithanya Kumar Mummadi et al.
Federated Wasserstein Distance
alain rakotomamonjy, Kimia Nadjahi, Liva Ralaivola
FedHyper: A Universal and Robust Learning Rate Scheduler for Federated Learning with Hypergradient Descent
Ziyao Wang, Jianyu Wang, Ang Li
FedImpro: Measuring and Improving Client Update in Federated Learning
Zhenheng Tang, Yonggang Zhang, Shaohuai Shi et al.
FedInverse: Evaluating Privacy Leakage in Federated Learning
DI WU, Jun Bai, Yiliao Song et al.
FedLoGe: Joint Local and Generic Federated Learning under Long-tailed Data
Zikai Xiao, Zihan Chen, Liyinglan Liu et al.
FedP3: Federated Personalized and Privacy-friendly Network Pruning under Model Heterogeneity
Kai Yi, Nidham Gazagnadou, Peter Richtarik et al.
FedTrans: Client-Transparent Utility Estimation for Robust Federated Learning
Mingkun Yang, Ran Zhu, Qing Wang et al.
FedWon: Triumphing Multi-domain Federated Learning Without Normalization
Weiming Zhuang, Lingjuan Lyu
Ferret: Refer and Ground Anything Anywhere at Any Granularity
Haoxuan You, Haotian Zhang, Zhe Gan et al.
Few-Shot Detection of Machine-Generated Text using Style Representations
Rafael Rivera Soto, Kailin Koch, Aleem Khan et al.
Few-shot Hybrid Domain Adaptation of Image Generator
Hengjia Li, Yang Liu, Linxuan Xia et al.
FFB: A Fair Fairness Benchmark for In-Processing Group Fairness Methods
Xiaotian Han, Jianfeng Chi, Yu Chen et al.
f-FERM: A Scalable Framework for Robust Fair Empirical Risk Minimization
Sina Baharlouei, Shivam Patel, Meisam Razaviyayn
Fiber Monte Carlo
Nick Richardson, Deniz Oktay, Yaniv Ovadia et al.
Fine-Tuned Language Models Generate Stable Inorganic Materials as Text
Nate Gruver, Anuroop Sriram, Andrea Madotto et al.
Fine-tuning Aligned Language Models Compromises Safety, Even When Users Do Not Intend To!
Xiangyu Qi, Yi Zeng, Tinghao Xie et al.
Fine-Tuning Enhances Existing Mechanisms: A Case Study on Entity Tracking
Nikhil Prakash, Tamar Shaham, Tal Haklay et al.
Fine-Tuning Language Models for Factuality
Katherine Tian, Eric Mitchell, Huaxiu Yao et al.
Fine-tuning Multimodal LLMs to Follow Zero-shot Demonstrative Instructions
Juncheng Li, Kaihang Pan, Zhiqi Ge et al.
Finetuning Text-to-Image Diffusion Models for Fairness
Xudong Shen, Chao Du, Tianyu Pang et al.
Finite Scalar Quantization: VQ-VAE Made Simple
Fabian Mentzer, David Minnen, Eirikur Agustsson et al.
Finite-State Autoregressive Entropy Coding for Efficient Learned Lossless Compression
Yufeng Zhang, Hang Yu, Jianguo Li et al.
Finite-Time Analysis of On-Policy Heterogeneous Federated Reinforcement Learning
Chenyu Zhang, Han Wang, Aritra Mitra et al.
First-order ANIL provably learns representations despite overparametrisation
Oğuz Kaan Yüksel, Etienne Boursier, Nicolas Flammarion
FITS: Modeling Time Series with $10k$ Parameters
Zhijian Xu, Ailing Zeng, Qiang Xu
Fixed-Budget Differentially Private Best Arm Identification
Zhirui Chen, P. N. Karthik, Yeow Meng Chee et al.
Fixed Non-negative Orthogonal Classifier: Inducing Zero-mean Neural Collapse with Feature Dimension Separation
Hoyong Kim, Kangil Kim
Flag Aggregator: Scalable Distributed Training under Failures and Augmented Losses using Convex Optimization
Hamidreza Almasi, Harsh Mishra, Balajee Vamanan et al.
FlashAttention-2: Faster Attention with Better Parallelism and Work Partitioning
Tri Dao
FlashFFTConv: Efficient Convolutions for Long Sequences with Tensor Cores
Dan Fu, Hermann Kumbong, Eric Nguyen et al.
FLASK: Fine-grained Language Model Evaluation based on Alignment Skill Sets
Seonghyeon Ye, Doyoung Kim, Sungdong Kim et al.
Flat Minima in Linear Estimation and an Extended Gauss Markov Theorem
Simon Segert