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