Extreme-value theory applied to false-alarm probabilities (Corresp.). - Terrence L. Fine; Morris J. Levin (IRE Trans. Inf. Theory, 1962)

Properties of an optimum digital system and applications. - Terrence L. Fine (IEEE Trans. Inf. Theory, 1964)

Optimum mean-square quantization of a noisy input (Corresp.). - Terrence L. Fine (IEEE Trans. Inf. Theory, 1965)

Optimum search for the location of the maximum of a unimodal function. - Terrence L. Fine (IEEE Trans. Inf. Theory, 1966)

The response of a particular nonlinear system with feedback to each of two random processes. - Terrence L. Fine (IEEE Trans. Inf. Theory, 1968)

On the apparent convergence of relative frequency and its implications. - Terrence L. Fine (IEEE Trans. Inf. Theory, 1970)

Extrapolation When Very Little is Known about the Source - Terrence Fine (Inf. Control., 1970)

Stochastic Independence and Computational Complexity. - Terrence Fine (IFIP Congress (1), 1971)

Review of 'Utility Theory for Decision Making' (Fishburn, P. C.; 1970). - Terrence L. Fine (IEEE Trans. Inf. Theory, 1972)

Uniformly reasonable source encoding is often practically impossible. - Terrence L. Fine (IEEE Trans. Inf. Theory, 1975)

Review of 'An Introduction to Statistical Signal Processing with Application' (Srinath, M.D., and Rajasekaran, P. K.; 1979). - Terrence L. Fine (IEEE Trans. Inf. Theory, 1980)

Designing Linear Threshold Based Neural Network Pattern Classifiers. - Terrence Fine (NIPS, 1990)

Forecasting Demand for Electric Power. - Jen-Lun Yuan; Terrence Fine (NIPS, 1992)

Asymptotics of Gradient-based Neural Network Training Algorithms. - Sayandev Mukherjee; Terrence Fine (NIPS, 1994)

Sample Size Requirements for Feedforward Neural Networks. - Michael J. Turmon; Terrence Fine (NIPS, 1994)

Ensemble pruning algorithms for accelerated training. - Sayandev Mukherjee; Terrence L. Fine (ICNN, 1996)

Adaptive blind equalization using artificial neural networks. - Chiu Fai Wong; Terrence L. Fine (ICNN, 1996)

Online Steepest Descent Yields Weights with Nonnormal Limiting Distribution. - Sayandev Mukherjee; Terrence L. Fine (Neural Comput., 1996)

Review of 'Fundamentals of Artificial Neural Networks' (Hassoun, M.H.; 1995). - Terrence L. Fine (IEEE Trans. Inf. Theory, 1996)

Neural-network design for small training sets of high dimension. - Jen-Lun Yuan; Terrence L. Fine (IEEE Trans. Neural Networks, 1998)

Parameter Convergence and Learning Curves for Neural Networks. - Terrence Fine; Sayandev Mukherjee (Neural Comput., 1999)

Towards a Frequentist Interpretation of Sets of Measures. - Pablo Ignacio Fierens; Terrence Fine (ISIPTA, 2001)

A new ICA algorithm for blind source separation. - Chin-Jen Ku; Terrence L. Fine (ICASSP (5), 2003)

Towards a Chaotic Probability Model for Frequentist Probability: The Univariate Case. - Pablo Ignacio Fierens; Terrence L. Fine (ISIPTA, 2003)

Optimal power and retransmission control policies for random access systems. - Guillermo del Angel; Terrence L. Fine (IEEE/ACM Trans. Netw., 2004)

Estimation of Chaotic Probabilities. - Leandro Chaves Rêgo; Terrence L. Fine (ISIPTA, 2005)

Information capacity and power control for slotted Aloha random-access systems. - Guillermo del Angel; Terrence L. Fine (IEEE Trans. Inf. Theory, 2005)

Testing for stochastic independence: application to blind source separation. - Chin-Jen Ku; Terrence L. Fine (IEEE Trans. Signal Process., 2005)

A Bayesian Independence Test for Small Datasets. - Chin-Jen Ku; Terrence L. Fine (IEEE Trans. Signal Process., 2006)