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- Risi Kondor, Hy Truong Son, Horace Pan, Brandon Anderson, Shubhendu Trivedi
- ArXiv
- 2018

Most existing neural networks for learning graphs address permutation invariance by conceiving of the network as a message passing scheme, where each node sums the feature vectors coming from itsâ€¦ (More)

By learning a more distributed representation of the input space, clustering can be a powerful source of information for boosting the performance of predictive models. While such semi-supervisedâ€¦ (More)

- GÃ¡bor N. SÃ¡rkÃ¶zy, Fei Song, Endre SzemerÃ©di, Shubhendu Trivedi
- ArXiv
- 2012

In this paper we introduce a new clustering technique called Regularity Clustering. This new technique is based on the practical variants of the two constructive versions of the Regularity Lemma, aâ€¦ (More)

In typical assessment student are not given feedback, as it is harder to predict student knowledge if it is changing during testing. Intelligent Tutoring systems, that offer assistance while theâ€¦ (More)

Spectral Clustering is a graph theoretic technique to represent data in such a way that clustering on this new representation is reduced to a trivial task. It is especially useful in complex datasetsâ€¦ (More)

We formulate the problem of metric learning for k nearest neighbor classification as a large margin structured prediction problem, with a latent variable representing the choice of neighbors and theâ€¦ (More)

In recent years, the educational data mining and user modeling communities have been aggressively introducing models for predicting student performance on external measures such as standardized testsâ€¦ (More)

- Risi Kondor, Shubhendu Trivedi
- ICML
- 2018

then the activations in higher layers transform in a corresponding way fl â†¦ f â€² l fl(x) = fl(x âˆ’ t). Equivariance is important for multiple reasons: 1. It reduces the number of parameters that theâ€¦ (More)

Learning a more distributed representation of the input feature space is a powerful method to boost the performance of a given predictor. Often this is accomplished by partitioning the data intoâ€¦ (More)

- Shubhendu Trivedi, Zachary A. Pardos, Neil T. Heffernan
- ArXiv
- 2015

â€”We explore the utility of clustering in reducing error in various prediction tasks. Previous work has hinted at the improvement in prediction accuracy attributed to clustering algorithms if used toâ€¦ (More)