ICLR 2024PastEfficiency
5th Workshop on practical ML for limited/low resource settings
PML4LRS
- Submission deadline
- Feb 10, 2024, 11:59 UTCimported from OpenReview — check the website for extensions
- Submission portal
- OpenReview
- Notes
- Topics were auto-suggested and may be imprecise — edits welcome.
Accepted papers (52)
Fetched from OpenReview (v2) on 2026-06-10.
$\mathcal{D}^2$-Sparse: Navigating the low data learning regime with coupled sparse networks
A Low-Resource Framework for Detection of Large Language Model Contents
A variational framework for local learning with probabilistic latent representations
Addax: Memory-Efficient Fine-Tuning of Language Models with a Combination of Forward-Backward and Forward-Only Passes
ADVANCING ENTERPRISE SPATIO-TEMPORAL FORECASTING APPLICATIONS : DATA MINING MEETS INSTRUCTION TUNING OF LANGUAGE MODELS FOR MULTI-MODAL TIME SERIES ANALYSIS IN LOW-RESOURCE SETTINGS
Autoregressive activity prediction for low-data drug discovery
Better (pseudo-)labels for semi-supervised instance segmentation
Bridging Diversity and Uncertainty in Active learning with Self-Supervised Pre-Training
Conditional Transformer Fine-Tuning by Adaptive Layer Skipping
Constricting Normal Latent Space for Anomaly Detection with Normal-only Training Data
Defer-and-Fusion: Optimal Predictors that Incorporate Human Decisions
Distributed Inference Performance Optimization for LLMs on CPUs
Efficient Transfer Learning in Diffusion Models via Adversarial Noise
Energy Minimizing-based token merging for accelerating Transformers
Estimating Multi-cause Average Treatment Effects via Partial Cause Intervention
FacePhi: Lightweight Multimodal Large Language Model for Facial Landmark Emotion Recognition
Fiddler: CPU-GPU Orchestration for Fast Inference of Mixture-of-Experts Models
GaLore: Memory-Efficient LLM Training by Gradient Low-Rank Projection
GNN-VPA: A Variance-Preserving Aggregation Strategy for Graph Neural Networks
Graph Gaussian Processes for Efficient Robust Monte Carlo Tree Search
HADS: Hardware-Aware Deep Subnetworks
How to Parameterize Asymmetric Quantization Ranges for Quantization-Aware Training
Implicit Two-Tower Policies
Investigating the Impact of Quantization on Adversarial Robustness
LESS: LEARNING TO SELECT A STRUCTURED ARCHITECTURE OVER FILTER PRUNING AND LOW-RANK DECOMPOSITION
Majority or Minority: Data Imbalance Learning Method for Named Entity Recognition
Multi-model evaluation with labeled & unlabeled data
Multi-source Fully Test-Time Adaptation
NEURAL NETWORK COMPRESSION: THE FUNCTIONAL PERSPECTIVE
Oh! We Freeze: Improving Quantized Knowledge Distillation via Signal Propagation Analysis for Large Language Models
On Fairness Implications and Evaluations of Low-Rank Adaptation of Large Models
On the Surprising Efficacy of Distillation as an Alternative to Pre-Training Small Models
Outlier Weighed Layerwise Sparsity (OWL): A Missing Secret Sauce for Pruning LLMs to High Sparsity
PC-LoRA: Progressive Model Compression with Low Rank Adaptation
Precision-Driven Low-Resource Speech Synthesis For Bangla Text-To-Speech System
SCAN-Edge: Finding MobileNet-speed Hybrid Networks for Commodity Edge Devices
Select High-Level Features: Efficient Experts from a Hierarchical Classification Network
Selective Prediction for Semantic Segmentation under Distribution Shift
Sharpness-Aware Minimization (SAM) Improves Classification Accuracy of Bacterial Raman Spectral Data Enabling Portable Diagnostics
Smoothness-Adaptive Sharpness-Aware Minimization for Finding Flatter Minima
SparQ Attention: Bandwidth-Efficient LLM Inference
Sparsity for Communication-Efficient LoRA
SPI-GAN: Denoising Diffusion GANs with Straight-Path Interpolations
Squeezing Lemons with Hammers: An Evaluation of AutoML and Tabular Deep Learning for Data-Scarce Classification Applications
SSM Meets Video Diffusion Models: Efficient Video Generation with Structured State Spaces
Subspace-Configurable Networks
SUPClust: Active Learning at the Boundaries
TaCo: Enhancing Cross-Lingual Transfer for Low-Resource Languages in LLMs through Translation-Assisted Chain-of-Thought Processes
Text2Data: Low-Resource Data Generation with Textual Control
Towards Bandit-based Optimization for Automated Machine Learning
Towards Leveraging AutoML for Sustainable Deep Learning: A Multi-Objective HPO Approach on Deep Shift Neural Networks
Variance-reduced Zeroth-Order Methods for Fine-Tuning Language Models