Fetching the paper…
Reading the bibliography…
Many real-life decision-making situations allow further relevant information to be acquired at a specific cost, for example, in assessing the health status of a patient we may decide to take additional measurements such as diagnostic tests or imaging scans before making a final assessment.
On a measure of the information provided by an experiment
Lindley, D. V · 1956
Earlier work this paper cites.
Inference and missing data
Rubin, D. B · 1976
Earlier work this paper cites.
Maximum likelihood from incomplete data via the em algorithm
Dempster, A. P., Laird, N. M., and Rubin, D. B · 1977
Earlier work this paper cites.
Expected information as expected utility
Bernardo, J. M · 1979
Earlier work this paper cites.
Statistical analysis with missing data
Little, R. and Rubin, D · 1987
Earlier work this paper cites.
Information-based objective functions for active data selection
MacKay, D. J · 1992
Earlier work this paper cites.
The mnist database of handwritten digits
LeCun, Y · 1998
Earlier work this paper cites.
Employing em and pool-based active learning for text classification
McCallumzy, A. K. and Nigamy, K · 1998
Earlier work this paper cites.
Dealing with missing data
Scheffer, J · 2002
Earlier work this paper cites.
On active learning for data acquisition
Zheng, Z. and Padmanabhan, B · 2002
Earlier work this paper cites.
Latent dirichlet allocation
Blei, D. M., Ng, A. Y., and Jordan, M. I · 2003
Earlier work this paper cites.
Active feature-value acquisition for classifier induction
Melville, P., Saar-Tsechansky, M., Provost, F., and Mooney, R · 2004
Earlier work this paper cites.
URL https://www.cdc.gov/nchs/nhanes/
National health and nutrition examination survey, 2005 · 2005
Earlier work this paper cites.
Bayesian probabilistic matrix factorization using markov chain monte carlo
Salakhutdinov, R. and Mnih, A · 2008
Earlier work this paper cites.
Underutilization of information and knowledge in everyday medical practice: Evaluation of a computer-based solution
Zakim, D., Braun, N., Fritz, P., and Alscher, M. D · 2008
Cited alongside, same era.
Active feature-value acquisition
Saar-Tsechansky, M., Melville, P., and Provost, F · 2009
Cited alongside, same era.
Matchbox: Large scale bayesian recommendations
Stern, D., Herbrich, R., and Graepel, T · 2009
Cited alongside, same era.
Guaranteed rank minimization via singular value projection
Jain, P., Meka, R., and Dhillon, I. S · 2010
Cited alongside, same era.
Matrix completion from noisy entries
Keshavan, R. H., Montanari, A., and Oh, S · 2010
Cited alongside, same era.
Bayesian active learning for classification and preference learning
Houlsby, N., Huszár, F., Ghahramani, Z., and Lengyel, M · 2011
Hierarchical variational models
Ranganath, R., Tran, D., and Blei, D · 2016
Later among the works it cites.
Temporal regularized matrix factorization for high-dimensional time series prediction
Yu, H.-F., Rao, N., and Dhillon, I. S · 2016
Later among the works it cites.
UCI machine learning repository, 2017
Dheeru, D. and Karra Taniskidou, E · 2017
Later among the works it cites.
Multitask learning and benchmarking with clinical time series data
Harutyunyan, H., Khachatrian, H., Kale, D. C., and Galstyan, A · 2017
Later among the works it cites.
Knowing what to ask: A bayesian active learning approach to the surveying problem
Lewenberg, Y., Bachrach, Y., Paquet, U., and Rosenschein, J. S · 2017
Later among the works it cites.
Pointnet: Deep learning on point sets for 3d classification and segmentation
alphaXiv searches the wider corpus for related work and actual follow-ups.
alphaXiv is searching for related work…
Cited alongside, same era.
Collaborative topic modeling for recommending scientific articles
Wang, C. and Blei, D. M · 2011
Cited alongside, same era.
Active learning
Settles, B · 2012
Cited alongside, same era.
An efficient heuristic method for active feature acquisition and its application to protein-protein interaction prediction
Thahir, M., Sharma, T., and Ganapathiraju, M. K · 2012
Cited alongside, same era.
Content-based recommendations with poisson factorization
Gopalan, P. K., Charlin, L., and Blei, D · 2014
Cited alongside, same era.
Auto-encoding variational bayes
Kingma, D. P. and Welling, M · 2014
Cited alongside, same era.
Stochastic backpropagation and approximate inference in deep generative models
Rezende, D. J., Mohamed, S., and Wierstra, D · 2014
Cited alongside, same era.
Qi, C. R., Su, H., Mo, K., and Guibas, L. J · 2017
Later among the works it cites.
Deep sets
Zaheer, M., Kottur, S., Ravanbakhsh, S., Poczos, B., Salakhutdinov, R. R., and Smola, A. J · 2017
Later among the works it cites.
Advances in variational inference
Zhang, C., Butepage, J., Kjellstrom, H., and Mandt, S · 2017
Later among the works it cites.
Garnelo, M., Rosenbaum, D., Maddison, C. J., Ramalho, T., Saxton, D., Shanahan, M., Teh, Y. W., Rezende, D. J., and Eslami, S · 2018
Closest in time.
Simultaneous measurement imputation and outcome prediction for achilles tendon rupture rehabilitation
Hamesse, C., Ackermann, P., Kjellström, H., and Zhang, C · 2018
Closest in time.
Active feature acquisition with supervised matrix completion
Huang, S.-J., Xu, M., Xie, M.-K., Sugiyama, M., Niu, G., and Chen, S · 2018
Closest in time.
Handling incomplete heterogeneous data using vaes
Nazabal, A., Olmos, P. M., Ghahramani, Z., and Valera, I · 2018
Closest in time.
Joint active feature acquisition and classification with variable-size set encoding
Shim, H., Hwang, S. J., and Yang, E · 2018
Closest in time.
Conditional inference in pre-trained variational autoencoders via cross-coding
Wu, G., Domke, J., and Sanner, S · 2018
Closest in time.