Summary of Uplift Modeling Under Limited Supervision, by George Panagopoulos et al.
Uplift Modeling Under Limited Supervisionby George Panagopoulos, Daniele Malitesta, Fragkiskos D. Malliaros, Jun PangFirst submitted…
Summary of Scaling Up Ridge Regression For Brain Encoding in a Massive Individual Fmri Dataset, by Sana Ahmadi and Pierre Bellec and Tristan Glatard
Scaling up ridge regression for brain encoding in a massive individual fMRI datasetby Sana Ahmadi,…
Summary of Can Language Beat Numerical Regression? Language-based Multimodal Trajectory Prediction, by Inhwan Bae and Junoh Lee and Hae-gon Jeon
Can Language Beat Numerical Regression? Language-Based Multimodal Trajectory Predictionby Inhwan Bae, Junoh Lee, Hae-Gon JeonFirst…
Summary of Order Of Compression: a Systematic and Optimal Sequence to Combinationally Compress Cnn, by Yingtao Shen et al.
Order of Compression: A Systematic and Optimal Sequence to Combinationally Compress CNNby Yingtao Shen, Minqing…
Summary of Exploring the Potential Of Prototype-based Soft-labels Data Distillation For Imbalanced Data Classification, by Radu-andrei Rosu et al.
Exploring the potential of prototype-based soft-labels data distillation for imbalanced data classificationby Radu-Andrei Rosu, Mihaela-Elena…
Summary of Contrastive Learning For Regression on Hyperspectral Data, by Mohamad Dhaini et al.
Contrastive Learning for Regression on Hyperspectral Databy Mohamad Dhaini, Maxime Berar, Paul Honeine, Antonin Van…
Summary of Calibrating Bayesian Unet++ For Sub-seasonal Forecasting, by Busra Asan et al.
Calibrating Bayesian UNet++ for Sub-Seasonal Forecastingby Busra Asan, Abdullah Akgül, Alper Unal, Melih Kandemir, Gozde…
Summary of On the Rates Of Convergence For Learning with Convolutional Neural Networks, by Yunfei Yang et al.
On the rates of convergence for learning with convolutional neural networksby Yunfei Yang, Han Feng,…
Summary of Near-optimal Differentially Private Low-rank Trace Regression with Guaranteed Private Initialization, by Mengyue Zha
Near-Optimal differentially private low-rank trace regression with guaranteed private initializationby Mengyue ZhaFirst submitted to arxiv…
Summary of Active Learning For Regression Based on Wasserstein Distance and Groupsort Neural Networks, by Benjamin Bobbia and Matthias Picard
Active Learning for Regression based on Wasserstein distance and GroupSort Neural Networksby Benjamin Bobbia, Matthias…