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Dealbreaker: A Nonlinear Latent Variable Model for Educational Data
(2016)Proceedings of Machine Learning Research ~ Proceedings of the International Conference on Machine Learning, 20-22 June 2016, New York, New York, USAStatistical models of student responses on assessment questions, such as those in homeworks and exams, enable educators and computer-based personalized learning systems to gain insights into students' knowledge using machine learning. Popular student-response models, including the Rasch model and item response theory models, represent the probability of a student answering a question correctly using an affine function of latent factors. ...Conference Paper -
FPGA Design of a Coordinate Descent Data Detector for Large-Scale MU-MIMO
(2016)2016 IEEE International Symposium on Circuits and Systems (ISCAS)We propose a new, low-complexity data-detection algorithm and a corresponding high-throughput FPGA design for 3GPP LTE-based large-scale (or massive) multi-user (MU) multiple-input multiple-output (MIMO) wireless communication systems. Our algorithm performs approximate minimum mean-square error (MMSE) data detection using coordinate descent (CD), which enables near-MMSE performance at low computational complexity, even for systems with ...Conference Paper -
Nonlinear 1-Bit Precoding for Massive MU-MIMO with Higher-Order Modulation
(2016)2016 50th Asilomar Conference on Signals, Systems and ComputersMassive multi-user (MU) multiple-input multiple-output (MIMO) is widely believed to be a core technology for the upcoming fifth-generation (5G) wireless communication standards. The use of low-precision digital-to-analog converters (DACs) in MU-MIMO base stations is of interest because it reduces the power consumption, system costs, and raw baseband data rates. In this paper, we develop novel algorithms for downlink precoding in massive ...Conference Paper -
Decentralized Data Detection for Massive MU-MIMO on a Xeon Phi Cluster
(2016)2016 50th Asilomar Conference on Signals, Systems and ComputersConventional centralized data detection algorithms for massive multi-user multiple-input multiple-output (MU-MIMO) systems, such as minimum mean square error (MMSE) equalization, result in excessively high raw baseband data rates and computing complexity at the centralized processing unit. Hence, practical base-station (BS) designs for massive MU-MIMO that rely on state-of-the-art hardware processors and I/O interconnect standards must ...Conference Paper -
Optimally Discriminative Choice Sets in Discrete Choice Models: Application to Data-Driven Test Design
(2016)KDD '16: Proceedings of the 22nd ACM SIGKDD International Conference on Knowledge Discovery and Data MiningAugust 2016Difficult multiple-choice (MC) questions can be made easy by providing a set of answer options of which most are obviously wrong. In the education literature, a plethora of instructional guides exist for crafting a suitable set of wrong choices (distractors) that enable the assessment of the students' understanding. The art of MC question design thus hinges on the question-maker's experience and knowledge of the potential misconceptions. ...Conference Paper -
FPGA design of approximate semidefinite relaxation for data detection in large MIMO wireless systems
(2016)2016 IEEE International Symposium on Circuits and Systems (ISCAS)We propose a novel, near-optimal data detection algorithm and a corresponding FPGA design for large multiple-input multiple-output (MIMO) wireless systems. Our algorithm, referred to as TASER (short for triangular approximate semidefinite relaxation), relaxes the maximum-likelihood (ML) detection problem to a semidefinite program and solves a non-convex approximation using a preconditioned forward-backward splitting procedure. We show ...Conference Paper -
Biconvex Relaxation for Semidefinite Programming in Computer Vision
(2016)Lecture Notes in Computer Science ~ Computer Vision – ECCV 2016 14th European Conference, Amsterdam, The Netherlands, October 11-14, 2016, Proceedings, Part VISemidefinite programming (SDP) is an indispensable tool in computer vision, but general-purpose solvers for SDPs are often too slow and memory intensive for large-scale problems. Our framework, referred to as biconvex relaxation (BCR), transforms an SDP consisting of PSD constraint matrices into a specific biconvex optimization problem, which can then be approximately solved in the original, low-dimensional variable space at low complexity. ...Conference Paper -
Calibrated Self-Assessment
(2016)Proceedings of the International Conference on Educational Data Mining (EDM) (9th, Raleigh, North Carolina, June 29-July 2, 2016)Peer-grading is widely believed to be an inexpensive and scalable way to assess students in large classroom settings. In this paper, we propose calibrated self-grading as a more efficient alternative to peer grading. For self-grading, students assign themselves a grade that they think they deserve via an incentive-compatible mechanism that elicits maximally truthful judgements of performance. We show that the students' self-evaluation ...Conference Paper -
On the Performance of Mismatched Data Detection in Large MIMO Systems
(2016)2016 IEEE International Symposium on Information Theory (ISIT)We investigate the performance of mismatched data detection in large multiple-input multiple-output (MIMO) systems, where the prior distribution of the transmit signal used in the data detector differs from the true prior. To minimize the performance loss caused by this prior mismatch, we include a tuning stage into our recently-proposed large MIMO approximate message passing (LAMA) algorithm, which allows us to develop mismatched LAMA ...Conference Paper -
Optimal Ranking of Test Items using the Rasch Model
(2016)2016 54th Annual Allerton Conference on Communication, Control, and Computing (Allerton)We study the problem of ranking test items, i.e., the ordering of items according to the amount of information they provide on the latent trait of the respondents. We focus on educational applications, where instructors are interested in ranking questions so as to select a small set of informative questions in order to efficiently assess the students' understanding on the course material. Using the Rasch model for modeling student responses, ...Conference Paper