Proceedings of the 29th International Conference on Machine Learning (ICML-12)

Abstract

This is an index to the papers that appear in the Proceedings of the 29th International Conference on Machine Learning (ICML-12). The conference was held in Edinburgh, Scotland, June 27th - July 3rd, 2012.

Proceedings of the 29th International Conference on Machine Learning (ICML-12). Editors: John Langford and Joelle Pineau. Publisher: Omnipress, 2012

Cited by in corpus (62)

• Uncertainty Quantification in Scientific Machine Learning: Methods, Metrics, and Comparisons
• A Methodology to Derive Global Maps of Leaf Traits Using Remote Sensing and Climate Data
• Automated data processing and feature engineering for deep learning and big data applications: a survey
• Think Locally, Act Locally: The Detection of Small, Medium-Sized, and Large Communities in Large Networks
• On the Random Batch Method for second order interacting particle systems
• Learning the PE Header, Malware Detection with Minimal Domain Knowledge
• Word-Entity Duet Representations for Document Ranking
• Friend, Collaborator, Student, Manager: How Design of an AI-Driven Game Level Editor Affects Creators
• Deep Divergence-Based Approach to Clustering
• One Detector to Rule Them All: Towards a General Deepfake Attack Detection Framework
• 3D Bayesian Variational Full Waveform Inversion
• Machine learning for transient discovery in Pan-STARRS1 difference imaging
• A Diffusion model for POI recommendation
• Deep Learning in Business Analytics: A Clash of Expectations and Reality
• Active emulation of computer codes with Gaussian processes -- Application to remote sensing
• Dual Space Graph Contrastive Learning
• Deep learning for plasma tomography using the bolometer system at JET
• Combining pretrained CNN feature extractors to enhance clustering of complex natural images
• A Survey on the Densest Subgraph Problem and Its Variants
• U(1) symmetric recurrent neural networks for quantum state reconstruction
• MultiScale Probability Map guided Index Pooling with Attention-based learning for Road and Building Segmentation
• SMC Faster R-CNN: Toward a scene-specialized multi-object detector
• VN Network: Embedding Newly Emerging Entities with Virtual Neighbors
• Jensen-Shannon Divergence Based Novel Loss Functions for Bayesian Neural Networks
• NuPS: A Parameter Server for Machine Learning with Non-Uniform Parameter Access
• On Fair Selection in the Presence of Implicit and Differential Variance
• Physics-informed Information Field Theory for Modeling Physical Systems with Uncertainty Quantification
• A Retrieve-and-Read Framework for Knowledge Graph Link Prediction
• Relational hyperevent models for the coevolution of coauthoring and citation networks
• PDP: Physics-Based Character Animation via Diffusion Policy
• Physics-informed Tensor-train ConvLSTM for Volumetric Velocity Forecasting of Loop Current
• A Co-training Approach for Noisy Time Series Learning
• Identifying a Training-Set Attack's Target Using Renormalized Influence Estimation
• Wide flat minima and optimal generalization in classifying high-dimensional Gaussian mixtures
• Modeling Dual Period-Varying Preferences for Takeaway Recommendation
• Learning to Rank Using Localized Geometric Mean Metrics
• Diffuse-CLoC: Guided Diffusion for Physics-based Character Look-ahead Control
• Deep Learning Approach for Matrix Completion Using Manifold Learning
• Continuous Time Graph Processes with Known ERGM Equilibria: Contextual Review, Extensions, and Synthesis
• Data Poisoning Attacks to Locally Differentially Private Frequent Itemset Mining Protocols
• Injection Optimization at Particle Accelerators via Reinforcement Learning: From Simulation to Real-World Application
• Exact Gauss-Newton Optimization for Training Deep Neural Networks
• Single- to multi-fidelity history-dependent learning with uncertainty quantification and disentanglement: application to data-driven constitutive modeling
• Neural Network Approach to Scaling Analysis of Critical Phenomena
• Linear processes in high-dimension: phase space and critical properties
• Unified Dual-Intent Translation for Joint Modeling of Search and Recommendation
• AdapMTL: Adaptive Pruning Framework for Multitask Learning Model
• An adaptive Hessian approximated stochastic gradient MCMC method
• Refinement of Hottopixx Method for Nonnegative Matrix Factorization Under Noisy Separability
• Stochastic Super-resolution of Cosmological Simulations with Denoising Diffusion Models
• Reviving the Context: Camera Trap Species Classification as Link Prediction on Multimodal Knowledge Graphs
• DAGPrompT: Pushing the Limits of Graph Prompting with a Distribution-aware Graph Prompt Tuning Approach
• Benchmarking the Fairness of Image Upsampling Methods
• A Bayesian Neural Network Approach for Tropospheric Temperature Retrievals from a Lidar Instrument
• Towards Safe Synthetic Image Generation On the Web: A Multimodal Robust NSFW Defense and Million Scale Dataset
• Learning-Based Design of Off-Policy Gaussian Controllers: Integrating Model Predictive Control and Gaussian Process Regression
• Regularized Unconstrained Weakly Submodular Maximization
• ReFrame: Rectification Framework for Image Explaining Architectures
• Benchmarking Recommendation, Classification, and Tracing Based on Hugging Face Knowledge Graph
• Real-Time Cleaning and Refinement of Facial Animation Signals
• Reinforcement Learning with Partial Parametric Model Knowledge
• Towards Designing Social Interventions For Online Climate Change Denialism Discussions