Thomas Hofmann

Joachim M. Buhmann, Thomas Hofmann, 1994, Proceedings of the 12th IAPR International Conference on Pattern Recognition, Vol. 3 - Conference C: Signal Processing (Cat. No.94CH3440-5).

A selective attention multi-chip system with dynamic synapses and spiking neurons

Thomas Hofmann, Bernhard Schölkopf, John Platt, 2007 .

A Deterministic Annealing Framework for Unsupervised Texture Segmentation

Joachim M. Buhmann, Thomas Hofmann, Jan Puzicha, 1996 .

Temporal dynamics of information content carried by neurons in the primary visual cortex

Thomas Hofmann, Bernhard Schölkopf, John Platt, 2007 .

Multiple-Instance Learning via Disjunctive Programming Boosting

Thomas Hofmann, Stuart Andrews, Thomas Hofmann, 2003, NIPS.

In-Network PCA and Anomaly Detection

Thomas Hofmann, Bernhard Schölkopf, John Platt, 2007 .

Hidden Markov Support Vector Machines

Thomas Hofmann, Yasemin Altun, Ioannis Tsochantaridis, 2003, ICML.

Hand-held transmitter, in particular for a toy model remote control

Thomas Hofmann, Ralph Bruder, Nils Tiemann, 2004 .

Ordinal Regression by Extended Binary Classification

Thomas Hofmann, Bernhard Schölkopf, John Platt, 2007 .

Topic-based language models using EM

Thomas Hofmann, Daniel Gildea, Thomas Hofmann, 1999, EUROSPEECH.

Text classification in a hierarchical mixture model for small training sets

Thomas Hofmann, Kristina Toutanova, Kris Popat, 2001, CIKM '01.

Probabilistic Topic Maps: Navigating through Large Text Collections

Thomas Hofmann, Thomas Hofmann, 1999, IDA.

Optimized communication method radiounderstöttede traffic services

Thomas Hofmann, Volker Pliquett, Fabrice Stein, 1999 .

Advanced experimental and numerical methods for the analysis of the dynamic forming press behavior

Thomas Hofmann, Peter Groche, Hajo Wiemer, 2007, Prod. Eng..

Inferring Network Structure from Co-Occurrences

Thomas Hofmann, Bernhard Schölkopf, John Platt, 2007 .

Optimized communication method for radio-based transport services

Thomas Hofmann, Volker Pliquett, Fabrice Stein, 1999 .

Proceedings of the 2011 European conference on Machine learning and knowledge discovery in databases - Volume Part III

Donato Malerba, Dimitrios Gunopulos, Thomas Hofmann, 2011 .

Bayesian Detection of Infrequent Differences in Sets of Time Series with Shared Structure

Thomas Hofmann, Bernhard Schölkopf, John Platt, 2007 .

Hyperbolic Neural Networks

Thomas Hofmann, Gary Bécigneul, Octavian-Eugen Ganea, 2018, NeurIPS.

Cross System Personalization and Collaborative Filtering by Learning Manifold Alignments

Thomas Hofmann, Bhaskar Mehta, 2006, KI.

Statistical Models for Co-occurrence Data

Thomas Hofmann, Jan Puzicha, Thomas Hofmann, 1998 .

Boosting Structured Prediction for Imitation Learning

Thomas Hofmann, Bernhard Schölkopf, John Platt, 2007 .

Non-redundant data clustering

Thomas Hofmann, David Gondek, 2006, Knowledge and Information Systems.

Multi-Instance Multi-Label Learning with Application to Scene Classification

Thomas Hofmann, Bernhard Schölkopf, John Platt, 2007 .

Conditional Information Bottleneck Clustering

Thomas Hofmann, David Gondek, Thomas Hofmann, 2008 .

Game Theoretic Algorithms for Protein-DNA binding

Thomas Hofmann, Bernhard Schölkopf, John Platt, 2007 .

Kernel Methods for Missing Variables

Thomas Hofmann, Alexander J. Smola, S. V. N. Vishwanathan, 2005, AISTATS.

Trading off Accuracy for Speed in PowerDrill

Thomas Hofmann, Reimar Hofmann, Alex Hall, 2016 .

Sparse Representation for Signal Classification

Thomas Hofmann, Bernhard Schölkopf, John Platt, 2007 .

Implicit Online Learning with Kernels

Thomas Hofmann, Bernhard Schölkopf, John Platt, 2007 .

Non-redundant data clustering

Thomas Hofmann, David Gondek, Thomas Hofmann, 2004, Fourth IEEE International Conference on Data Mining (ICDM'04).

Efficient Subwindow Search: A Branch and Bound Framework for Object Localization

Christoph H. Lampert, Thomas Hofmann, Matthew B. Blaschko, 2009, IEEE Transactions on Pattern Analysis and Machine Intelligence.

Denoising and Dimension Reduction in Feature Space

Thomas Hofmann, Bernhard Schölkopf, John Platt, 2007 .

Learning Time-Intensity Profiles of Human Activity using Non-Parametric Bayesian Models

Thomas Hofmann, Bernhard Schölkopf, John Platt, 2007 .

An Online Learning Approach to Generative Adversarial Networks pdf

Andreas Krause, Thomas Hofmann, Aurélien Lucchi, 2017, ICLR.

A brain computer interface with online feedback based on magnetoencephalography

Thomas Hofmann, Bernhard Schölkopf, Wolfgang Rosenstiel, 2005, ICML.

Deep Joint Entity Disambiguation with Local Neural Attention pdf

Thomas Hofmann, Octavian-Eugen Ganea, Thomas Hofmann, 2017, EMNLP.

Sparse Kernel Orthonormalized PLS for feature extraction in large data sets

Thomas Hofmann, Bernhard Schölkopf, John Platt, 2007 .

Support vector machine learning for interdependent and structured output spaces

Thomas Hofmann, Thorsten Joachims, Yasemin Altun, 2004, ICML.

Structured Prediction Based on Discriminative Models

Gökhan BakIr, Thomas Hofmann, Bernhard Schölkopf, 2007 .

AdaBoost is Consistent

Thomas Hofmann, Bernhard Schölkopf, John Platt, 2007 .

Convergence of Laplacian Eigenmaps

Thomas Hofmann, Bernhard Schölkopf, John Platt, 2007 .

Exponential convergence rates for Batch Normalization: The power of length-direction decoupling in non-convex optimization

Thomas Hofmann, Ming Zhou, Aurélien Lucchi, 2018, AISTATS.

Hierarchical document categorization with support vector machines

Thomas Hofmann, Lijuan Cai, Thomas Hofmann, 2004, CIKM '04.

Text categorization by boosting automatically extracted concepts

Thomas Hofmann, Lijuan Cai, Thomas Hofmann, 2003, SIGIR.

The Odds are Odd: A Statistical Test for Detecting Adversarial Examples

Thomas Hofmann, Yannic Kilcher, Kevin Roth, 2019, ICML.

NEW HMI Möglichkeiten und Grenzen abstrakt-geographischer Visualisierung in Bereich der Anlagensteuerung

Thomas Hofmann, Peter Holzkämper, 2008, Usability Professionals.

Reducing Calibration Time For Brain-Computer Interfaces: A Clustering Approach

Thomas Hofmann, Bernhard Schölkopf, John Platt, 2007 .

A Collapsed Variational Bayesian Inference Algorithm for Latent Dirichlet Allocation

Thomas Hofmann, Bernhard Schölkopf, John Platt, 2007 .

Unified Inference for Variational Bayesian Linear Gaussian State-Space Models

Thomas Hofmann, Bernhard Schölkopf, John Platt, 2007 .

Adversarially Robust Training through Structured Gradient Regularization pdf

Sebastian Nowozin, Thomas Hofmann, Aurélien Lucchi, 2018, ArXiv.

Detecting Humans via Their Pose

Thomas Hofmann, Bernhard Schölkopf, John Platt, 2007 .

A Variance Reduced Stochastic Newton Method pdf

Thomas Hofmann, Aurélien Lucchi, Brian McWilliams, 2015, ArXiv.

Energy-Based Models

Gökhan BakIr, Thomas Hofmann, Bernhard Schölkopf, 2007 .

Fast Discriminative Visual Codebooks using Randomized Clustering Forests

Thomas Hofmann, Bernhard Schölkopf, John Platt, 2007 .

Deterministic Annealing for Unsupervised Texture Segmentation

Joachim M. Buhmann, Thomas Hofmann, Jan Puzicha, 1997, EMMCVPR.

Tighter PAC-Bayes Bounds

Thomas Hofmann, Bernhard Schölkopf, John Platt, 2007 .

Single Channel Speech Separation Using Factorial Dynamics

Thomas Hofmann, Bernhard Schölkopf, John Platt, 2007 .

The Neurodynamics of Belief Propagation on Binary Markov Random Fields

Thomas Hofmann, Bernhard Schölkopf, John Platt, 2007 .

Machine Learning and Knowledge Discovery in Databases

Donato Malerba, Dimitrios Gunopulos, Thomas Hofmann, 2017, Lecture Notes in Computer Science.

Probabilistic Latent Semantic Analysis

Thomas Hofmann, Thomas Hofmann, 1999, UAI.

Challenges in information retrieval and language modeling: report of a workshop held at the center for intelligent information retrieval, University of Massachusetts Amherst, September 2002

Djoerd Hiemstra, Alan F. Smeaton, Nicholas J. Belkin, 2003, SIGF.

Temporal Coding using the Response Properties of Spiking Neurons

Thomas Hofmann, Bernhard Schölkopf, John Platt, 2007 .

Active learning for misspecified generalized linear models

Thomas Hofmann, Bernhard Schölkopf, John Platt, 2007 .

Adaptor Grammars: A Framework for Specifying Compositional Nonparametric Bayesian Models

Thomas Hofmann, Bernhard Schölkopf, John Platt, 2007 .

Exploiting Known Taxonomies in Learning Overlapping Concepts

Thomas Hofmann, Lijuan Cai, Xiaofei He, 2007, IJCAI.

Pairwise Data Clustering by Deterministic Annealing

Joachim M. Buhmann, Thomas Hofmann, J. Buhmann, 1997, IEEE Trans. Pattern Anal. Mach. Intell..

Support Vector Machines for Multiple-Instance Learning

Thomas Hofmann, Stuart Andrews, Ioannis Tsochantaridis, 2002, NIPS.

Online Classification for Complex Problems Using Simultaneous Projections

Thomas Hofmann, Bernhard Schölkopf, John Platt, 2007 .

The Missing Link - A Probabilistic Model of Document Content and Hypertext Connectivity

David A. Cohn, Thomas Hofmann, Thomas Hofmann, 2000, NIPS.

Stochastic Relational Models for Discriminative Link Prediction

Thomas Hofmann, Bernhard Schölkopf, John Platt, 2007 .

Statistical Modeling of Images with Fields of Gaussian Scale Mixtures

Thomas Hofmann, Bernhard Schölkopf, John Platt, 2007 .

Learning probabilistic models of the Web (poster session)

Thomas Hofmann, 2000, SIGIR '00.

Scalable Discriminative Learning for Natural Language Parsing and Translation

Thomas Hofmann, Bernhard Schölkopf, John Platt, 2007 .

The Mobile Robot Rhino

Wolfram Burgard, Joachim M. Buhmann, Armin B. Cremers, 1995, SNN Symposium on Neural Networks.

iLSTD: Eligibility Traces and Convergence Analysis

Thomas Hofmann, Bernhard Schölkopf, John Platt, 2007 .

Neighborhood Watch: Stochastic Gradient Descent with Neighbors pdf

Thomas Hofmann, Aurélien Lucchi, Brian McWilliams, 2015, ArXiv.

Beyond sliding windows: Object localization by efficient subwindow search

Christoph H. Lampert, Thomas Hofmann, Matthew B. Blaschko, 2008, 2008 IEEE Conference on Computer Vision and Pattern Recognition.

Conformal Multi-Instance Kernels

Thomas Hofmann, Matthew B. Blaschko, Thomas Hofmann, 2006, NIPS 2006.

An EM Algorithm for Localizing Multiple Sound Sources in Reverberant Environments

Thomas Hofmann, Bernhard Schölkopf, John Platt, 2007 .

Analysis of Empirical Bayesian Methods for Neuroelectromagnetic Source Localization

Thomas Hofmann, Bernhard Schölkopf, John Platt, 2007 .

Real-time adaptive information-theoretic optimization of neurophysiology experiments

Thomas Hofmann, Bernhard Schölkopf, John Platt, 2007 .

Non-parametric similarity measures for unsupervised texture segmentation and image retrieval

Joachim M. Buhmann, Thomas Hofmann, Jan Puzicha, 1997, Proceedings of IEEE Computer Society Conference on Computer Vision and Pattern Recognition.

Speakers optimize information density through syntactic reduction

Thomas Hofmann, Bernhard Schölkopf, John Platt, 2007 .

Zero-Shot Dual Machine Translation pdf

Thomas Hofmann, Massimiliano Ciaramita, Christian Buck, 2018, ArXiv.

Data Integration for Classification Problems Employing Gaussian Process Priors

Thomas Hofmann, Bernhard Schölkopf, John Platt, 2007 .

Automated Hierarchy Discovery for Planning in Partially Observable Environments

Thomas Hofmann, Bernhard Schölkopf, John Platt, 2007 .

Nonlinear physically-based models for decoding motor-cortical population activity

Thomas Hofmann, Bernhard Schölkopf, John Platt, 2007 .

Discrete Mixture Models for Unsupervised Image Segmentation

Joachim M. Buhmann, Thomas Hofmann, Jan Puzicha, 1998, DAGM-Symposium.

Bootstrap, Review, Decode: Using Out-of-Domain Textual Data to Improve Image Captioning pdf

Wenhu Chen, Thomas Hofmann, Aurélien Lucchi, 2016, ArXiv.

Attribute-efficient learning of decision lists and linear threshold functions under unconcentrated distributions

Thomas Hofmann, Bernhard Schölkopf, John Platt, 2007 .

Probabilistic latent semantic indexing

Thomas Hofmann, Thomas Hofmann, 1999, SIGIR '99.

Collaborative Machine Learning

Thomas Hofmann, Justin Basilico, 2005, From Integrated Publication and Information Systems to Virtual Information and Knowledge Environments.

Semantic Place Descriptors for Classification and Map Discovery pdf

Thomas Hofmann, Carsten Eickhoff, Siddharth Sarda, 2016, ArXiv.

Dirichlet-Enhanced Spam Filtering based on Biased Samples

Thomas Hofmann, Bernhard Schölkopf, John Platt, 2007 .

Greedy Layer-Wise Training of Deep Networks

Thomas Hofmann, Bernhard Schölkopf, John Platt, 2007 .

A Distributed Second-Order Algorithm You Can Trust

Thomas Hofmann, Aurélien Lucchi, Martin Jaggi, 2018, ICML.

Gaussian process classification for segmenting and annotating sequences

Thomas Hofmann, Alexander J. Smola, Yasemin Altun, 2004, ICML.

Clustering appearance and shape by learning jigsaws

Thomas Hofmann, Bernhard Schölkopf, John Platt, 2007 .

Analysis of Representations for Domain Adaptation

Thomas Hofmann, Bernhard Schölkopf, John Platt, 2007 .

Lies and propaganda: detecting spam users in collaborative filtering

Thomas Hofmann, Peter Fankhauser, Bhaskar Mehta, 2007, IUI '07.

Bayesian Policy Gradient Algorithms

Thomas Hofmann, Bernhard Schölkopf, John Platt, 2007 .

Thomas Hofmann, Thomas Hofmann, 1999, NIPS.

Exponential Families for Conditional Random Fields pdf

Thomas Hofmann, Alexander J. Smola, Yasemin Altun, 2004, UAI.

Temporal and Cross-Subject Probabilistic Models for fMRI Prediction Tasks

Thomas Hofmann, Bernhard Schölkopf, John Platt, 2007 .

Support Vector Machines on a Budget

Thomas Hofmann, Bernhard Schölkopf, John Platt, 2007 .

Efficient sparse coding algorithms

Thomas Hofmann, Bernhard Schölkopf, John Platt, 2007 .

Learning from Dyadic Data

Thomas Hofmann, Michael I. Jordan, Jan Puzicha, 1998, NIPS.

Semi-supervised Learning on Directed Graphs

Thomas Hofmann, Bernhard Schölkopf, Dengyong Zhou, 2004, NIPS.

PAC-Bayes Bounds for the Risk of the Majority Vote and the Variance of the Gibbs Classifier

Thomas Hofmann, Bernhard Schölkopf, John Platt, 2007 .

Latent Class Models for Collaborative Filtering

Thomas Hofmann, Jan Puzicha, Thomas Hofmann, 1999, IJCAI.

The Cluster-Abstraction Model: Unsupervised Learning of Topic Hierarchies from Text Data

Thomas Hofmann, Thomas Hofmann, 1999, IJCAI.

Causal inference in sensorimotor integration

Thomas Hofmann, Bernhard Schölkopf, John Platt, 2007 .

Map learning and high-speed navigation in RHINO

Wolfram Burgard, Thomas Hofmann, Sebastian Thrun, 1998 .

Learning to Model Spatial Dependency: Semi-Supervised Discriminative Random Fields

Thomas Hofmann, Bernhard Schölkopf, John Platt, 2007 .

Learning Structural Equation Models for fMRI

Thomas Hofmann, Bernhard Schölkopf, John Platt, 2007 .

Map-Reduce for Machine Learning on Multicore

Thomas Hofmann, Bernhard Schölkopf, John Platt, 2007 .

Generalization Bounds and Consistency for Structured Labeling

Gökhan BakIr, Thomas Hofmann, Bernhard Schölkopf, 2007 .

Unsupervised Learning by Probabilistic Latent Semantic Analysis

Thomas Hofmann, Thomas Hofmann, 2004, Machine Learning.

Deep State Space Models for Unconditional Word Generation

Thomas Hofmann, Florian Schmidt, Thomas Hofmann, 2018, NeurIPS.

From bits and bytes to information and knowledge

Thomas Hofmann, 2005, CIKM '05.

An Annealed "Neural Gas" Network for Robust Vector Quantization

Joachim M. Buhmann, Thomas Hofmann, 1996, ICANN.

Robotic Grasping of Novel Objects

Thomas Hofmann, Bernhard Schölkopf, John Platt, 2007 .

Processing system, method for operating a processing facility and use of a processing facility

Thomas Hofmann, Peter Holzkämper, 2014 .

Discriminative Methods for Label Sequence Learning

Thomas Hofmann, Yasemin Altun, Thomas Hofmann, 2005 .

A Semi-supervised Framework for Image Captioning

Wenhu Chen, Thomas Hofmann, Aurelien Lucchi, 2016 .

Unsupervised segmentation of textured images by pairwise data clustering

Joachim M. Buhmann, Thomas Hofmann, Jan Puzicha, 1996, Proceedings of 3rd IEEE International Conference on Image Processing.

Investigating Loss Functions and Optimization Methods for Discriminative Learning of Label Sequences

Thomas Hofmann, Mark Johnson, Yasemin Altun, 2003, EMNLP.

Natural Actor-Critic for Road Traffic Optimisation

Thomas Hofmann, Bernhard Schölkopf, John Platt, 2007 .

Fully Character-Level Neural Machine Translation without Explicit Segmentation

Jason Lee, Thomas Hofmann, Kyunghyun Cho, 2016, TACL.

Stabilizing Training of Generative Adversarial Networks through Regularization

Sebastian Nowozin, Thomas Hofmann, Aurélien Lucchi, 2017, NIPS.

Probabilistic Latent Semantic Indexing

Thomas Hofmann, Thomas Hofmann, 1999, SIGIR Forum.

Advances in Neural Information Processing Systems 19: Proceedings of the 2006 Conference (Bradford Books)

Thomas Hofmann, Bernhard Schölkopf, John Platt, 2007 .

Attentional Processing on a Spike-Based VLSI Neural Network

Thomas Hofmann, Bernhard Schölkopf, John Platt, 2007 .

TrueSkill™: A Bayesian Skill Rating System

Thomas Hofmann, Bernhard Schölkopf, John Platt, 2007 .

Optimal Change-Detection and Spiking Neurons

Thomas Hofmann, Bernhard Schölkopf, John Platt, 2007 .

Multiple instance learning with generalized support vector machines

Thomas Hofmann, Stuart Andrews, Ioannis Tsochantaridis, 2002, AAAI/IAAI.

An optimization approach to unsupervised hierarchical texture segmentation

Joachim M. Buhmann, Thomas Hofmann, Jan Puzicha, 1997, Proceedings of International Conference on Image Processing.

A theory of proximity based clustering: structure detection by optimization

Joachim M. Buhmann, Thomas Hofmann, Jan Puzicha, 2000, Pattern Recognit..

Efficient Learning of Sparse Representations with an Energy-Based Model

Thomas Hofmann, Bernhard Schölkopf, John Platt, 2007 .

Unifying collaborative and content-based filtering

Thomas Hofmann, Justin Basilico, Thomas Hofmann, 2004, ICML.

Semantic Interpolation in Implicit Models pdf

Thomas Hofmann, Aurélien Lucchi, Yannic Kilcher, 2018, ICLR.

Discriminative Learning for Label Sequences via Boosting

Thomas Hofmann, Mark Johnson, Yasemin Altun, 2002, NIPS.

Generalized Maximum Margin Clustering and Unsupervised Kernel Learning

Thomas Hofmann, Bernhard Schölkopf, John Platt, 2007 .

Cross System Personalization by Factor Analysis

Thomas Hofmann, Peter Fankhauser, Bhaskar Mehta, 2006 .

Introduction to the special issue on machine learning methods for text and images

Thomas Hofmann, Tomaso Poggio, Jaz S. Kandola, 2003 .

Predicting Structured Data (Neural Information Processing)

Thomas Hofmann, Bernhard Schölkopf, Alexander J. Smola, 2007 .

Non-redundant clustering with conditional ensembles

Thomas Hofmann, David Gondek, Thomas Hofmann, 2005, KDD '05.

A joint framework for collaborative and content filtering

Thomas Hofmann, Justin Basilico, 2004, SIGIR '04.

Information Bottleneck Optimization and Independent Component Extraction with Spiking Neurons

Thomas Hofmann, Bernhard Schölkopf, John Platt, 2007 .

ProbMap - A probabilistic approach for mapping large document collections

Thomas Hofmann, Thomas Hofmann, 2000, Intell. Data Anal..

Parameter Expanded Variational Bayesian Methods

Thomas Hofmann, Bernhard Schölkopf, John Platt, 2007 .

A Survey of Attack-Resistant Collaborative Filtering Algorithms

Thomas Hofmann, Bhaskar Mehta, Thomas Hofmann, 2008, IEEE Data Eng. Bull..

Machine Learning and Knowledge Discovery in Databases, Part III: European Conference, ECML PKDD 2010, Athens, Greece, September 5-9, 2011, ... / Lecture Notes in Artificial Intelligence)

Donato Malerba, Dimitrios Gunopulos, Thomas Hofmann, 2011 .

A Bayesian Approach to Diffusion Models of Decision-Making and Response Time

Thomas Hofmann, Bernhard Schölkopf, John Platt, 2007 .

Leveraging Large Amounts of Weakly Supervised Data for Multi-Language Sentiment Classification

Thomas Hofmann, Aurélien Lucchi, Martin Jaggi, 2017, WWW.

Histogram clustering for unsupervised image segmentation

Joachim M. Buhmann, Thomas Hofmann, Jan Puzicha, 1999, Proceedings. 1999 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (Cat. No PR00149).

Pattern Recognition, Statistical

Thomas Hofmann, Thomas Hofmann, 2006 .

A Review of Kernel Methods in Machine Learning

Thomas Hofmann, Bernhard Schölkopf, Alexander J. Smola, 2006 .

Global Biclustering of Microarray Data

Thomas Hofmann, Thomas Wolf, Elisabeth Georgii, 2006, Sixth IEEE International Conference on Data Mining - Workshops (ICDMW'06).

Fast cosmic web simulations with generative adversarial networks

Thomas Hofmann, Adam Amara, Aurelien Lucchi, 2018, Computational Astrophysics and Cosmology.

Learning to parse images of articulated bodies

Thomas Hofmann, Bernhard Schölkopf, John Platt, 2007 .

Relational Learning with Gaussian Processes

Thomas Hofmann, Bernhard Schölkopf, John Platt, 2007 .

A Cutting-Plane Algorithm for Learning from Ambiguous Examples

Thomas Hofmann, Stuart Andrews, 2006 .

The Robustness-Performance Tradeoff in Markov Decision Processes

Thomas Hofmann, Bernhard Schölkopf, John Platt, 2007 .

Inferring Hierarchical Clustering Structures by Deterministic Annealing

Joachim M. Buhmann, Thomas Hofmann, 1996, KDD.

Learning and Evaluating Sparse Interpretable Sentence Embeddings

Thomas Hofmann, Octavian-Eugen Ganea, Anna Potapenko, 2018, BlackboxNLP@EMNLP.

Learning Nonparametric Models for Probabilistic Imitation

Thomas Hofmann, Bernhard Schölkopf, John Platt, 2007 .

Learning Over Compact Metric Spaces

Thomas Hofmann, Ha Quang Minh, 2004, COLT.

Analysis of Contour Motions

Thomas Hofmann, Bernhard Schölkopf, John Platt, 2007 .

Robust collaborative filtering

Thomas Hofmann, Bhaskar Mehta, Wolfgang Nejdl, 2007, RecSys '07.

Accelerated Dual Learning by Homotopic Initialization pdf

Thomas Hofmann, Hamed Hassani, Hadi Daneshmand, 2017, ArXiv.

End-to-End Neural Entity Linking

Thomas Hofmann, Octavian-Eugen Ganea, Nikolaos Kolitsas, 2018, CoNLL.

Learning and representing topic-a hierarchical mixture model for word occurences in document databas

Thomas Hofmann, Thomas Hofmann, 1998 .

A Scalable Machine Learning Approach to Go

Thomas Hofmann, Bernhard Schölkopf, John Platt, 2007 .

Multi-dynamic Bayesian Networks

Thomas Hofmann, Bernhard Schölkopf, John Platt, 2007 .

Large Margin Multi-channel Analog-to-Digital Conversion with Applications to Neural Prosthesis

Thomas Hofmann, Bernhard Schölkopf, John Platt, 2007 .

Evaluation eines Human-Machine-Interface für Tower-Fluglotsen unter Einsatz eines Simulators

Thomas Hofmann, Christina König, Ralph Bruder, 2008, Usability Professionals.

Distributed Inference in Dynamical Systems

Thomas Hofmann, Bernhard Schölkopf, John Platt, 2007 .

Active Data Clustering

Joachim M. Buhmann, Thomas Hofmann, J. Buhmann, 1997, NIPS.

A Kernel Subspace Method by Stochastic Realization for Learning Nonlinear Dynamical Systems

Thomas Hofmann, Bernhard Schölkopf, John Platt, 2007 .

Unsupervised Learning of a Probabilistic Grammar for Object Detection and Parsing

Thomas Hofmann, Bernhard Schölkopf, John Platt, 2007 .

A Complexity-Distortion Approach to Joint Pattern Alignment

Thomas Hofmann, Bernhard Schölkopf, John Platt, 2007 .

DFS ConceptDesk—An Approach to an Intuitive UX for Air Traffic Control

Thomas Hofmann, Jörg Bergner, Robert Schnuell, 2016 .

Learning Curved Multinomial Subfamilies for Natural Language Processing and Information Retrieval

Thomas Hofmann, Keith B. Hall, Thomas Hofmann, 2000, ICML.

Robust vector quantization by competitive learning

Joachim M. Buhmann, Thomas Hofmann, 1997, 1997 IEEE International Conference on Acoustics, Speech, and Signal Processing.

Uniform Convergence, Adversarial Spheres and a Simple Remedy pdf

Thomas Hofmann, Seyed-Mohsen Moosavi-Dezfooli, Gregor Bachmann, 2021, ICML.

Disentangling the Roles of Curation, Data-Augmentation and the Prior in the Cold Posterior Effect pdf

Sebastian Nowozin, Thomas Hofmann, Kevin Roth, 2021, ArXiv.

Precise characterization of the prior predictive distribution of deep ReLU networks pdf

Sebastian Nowozin, Thomas Hofmann, Kevin Roth, 2021, NeurIPS.

How to Query Language Models? pdf

Thomas Hofmann, Leonard Adolphs, Shehzaad Dhuliawala, 2021, ArXiv.

Analytic Insights into Structure and Rank of Neural Network Hessian Maps pdf

Thomas Hofmann, Sidak Pal Singh, Gregor Bachmann, 2021, NeurIPS.

Boosting Search Engines with Interactive Agents pdf

Thomas Hofmann, Massimiliano Ciaramita, Yannic Kilcher, 2021, ArXiv.

Cosmological constraints from noisy convergence maps through deep learning

Thomas Hofmann, Adam Amara, Aurelien Lucchi, 2018, Physical Review D.

Deterministic Annealing: Fast Physical Heuristics for Real–Time Optimization of Large Systems

Joachim M. Buhmann, Thomas Hofmann, Jan Puzicha, 2007 .

Cosmological model discrimination with Deep Learning

Thomas Hofmann, Adam Amara, Aurelien Lucchi, 2017, 1707.05167.

Learning from ambiguous examples

Thomas Hofmann, Stuart Andrews, 2007 .

Cosmological constraints with deep learning from KiDS-450 weak lensing maps

Thomas Hofmann, Adam Amara, Aurelien Lucchi, 2019, Physical Review D.