Tommi S. Jaakkola

According to our database1, Tommi S. Jaakkola authored at least 184 papers between 1994 and 2021.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of two.

Timeline

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Bibliography

2021
Few-shot Conformal Prediction with Auxiliary Tasks.
CoRR, 2021

2020
Fundamental Limits and Tradeoffs in Invariant Representation Learning.
CoRR, 2020

Discovering Synergistic Drug Combinations for COVID with Biological Bottleneck Models.
CoRR, 2020

Graph Adversarial Networks: Protecting Information against Adversarial Attacks.
CoRR, 2020

Relaxed Conformal Prediction Cascades for Efficient Inference Over Many Labels.
CoRR, 2020

Improved Conditional Flow Models for Molecule to Image Synthesis.
CoRR, 2020

Optimal Transport Graph Neural Networks.
CoRR, 2020

Domain Extrapolation via Regret Minimization.
CoRR, 2020

Adaptive Invariance for Molecule Property Prediction.
CoRR, 2020

The Benefits of Pairwise Discriminators for Adversarial Training.
CoRR, 2020

Composing Molecules with Multiple Property Constraints.
CoRR, 2020

Improving Molecular Design by Stochastic Iterative Target Augmentation.
Proceedings of the 37th International Conference on Machine Learning, 2020

Educating Text Autoencoders: Latent Representation Guidance via Denoising.
Proceedings of the 37th International Conference on Machine Learning, 2020

Multi-Objective Molecule Generation using Interpretable Substructures.
Proceedings of the 37th International Conference on Machine Learning, 2020

Hierarchical Generation of Molecular Graphs using Structural Motifs.
Proceedings of the 37th International Conference on Machine Learning, 2020

Generalization and Representational Limits of Graph Neural Networks.
Proceedings of the 37th International Conference on Machine Learning, 2020

Predicting deliberative outcomes.
Proceedings of the 37th International Conference on Machine Learning, 2020

Invariant Rationalization.
Proceedings of the 37th International Conference on Machine Learning, 2020

Oblique Decision Trees from Derivatives of ReLU Networks.
Proceedings of the 8th International Conference on Learning Representations, 2020

Self-Supervised Learning of Appliance Usage.
Proceedings of the 8th International Conference on Learning Representations, 2020

Blank Language Models.
Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing, 2020

Unsupervised Hierarchy Matching with Optimal Transport over Hyperbolic Spaces.
Proceedings of the 23rd International Conference on Artificial Intelligence and Statistics, 2020

2019
High Dimensional Inference With Random Maximum A-Posteriori Perturbations.
IEEE Trans. Inf. Theory, 2019

Correction to Analyzing Learned Molecular Representations for Property Prediction.
J. Chem. Inf. Model., 2019

Analyzing Learned Molecular Representations for Property Prediction.
J. Chem. Inf. Model., 2019

Learning to Make Generalizable and Diverse Predictions for Retrosynthesis.
CoRR, 2019

Locally Constant Networks.
CoRR, 2019

Multi-resolution Autoregressive Graph-to-Graph Translation for Molecules.
CoRR, 2019

A Stratified Approach to Robustness for Randomly Smoothed Classifiers.
CoRR, 2019

Latent Space Secrets of Denoising Text-Autoencoders.
CoRR, 2019

Path-Augmented Graph Transformer Network.
CoRR, 2019

Strategic Prediction with Latent Aggregative Games.
CoRR, 2019

Are Learned Molecular Representations Ready For Prime Time?
CoRR, 2019

Alignment Based Matching Networks for One-Shot Classification and Open-Set Recognition.
CoRR, 2019

Direct Optimization through arg max for Discrete Variational Auto-Encoder.
Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

Tight Certificates of Adversarial Robustness for Randomly Smoothed Classifiers.
Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

Generative Models for Graph-Based Protein Design.
Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

Solving graph compression via optimal transport.
Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

A Game Theoretic Approach to Class-wise Selective Rationalization.
Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

Functional Transparency for Structured Data: a Game-Theoretic Approach.
Proceedings of the 36th International Conference on Machine Learning, 2019

Towards Robust, Locally Linear Deep Networks.
Proceedings of the 7th International Conference on Learning Representations, 2019

Learning Multimodal Graph-to-Graph Translation for Molecule Optimization.
Proceedings of the 7th International Conference on Learning Representations, 2019

Rethinking Cooperative Rationalization: Introspective Extraction and Complement Control.
Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing, 2019

Towards Optimal Transport with Global Invariances.
Proceedings of the 22nd International Conference on Artificial Intelligence and Statistics, 2019

Bidirectional Inference Networks: A Class of Deep Bayesian Networks for Health Profiling.
Proceedings of the Thirty-Third AAAI Conference on Artificial Intelligence, 2019

2018
Grounding Language for Transfer in Deep Reinforcement Learning.
J. Artif. Intell. Res., 2018

Learning Multimodal Graph-to-Graph Translation for Molecular Optimization.
CoRR, 2018

Game-Theoretic Interpretability for Temporal Modeling.
CoRR, 2018

On the Robustness of Interpretability Methods.
CoRR, 2018

The Variational Homoencoder: Learning to learn high capacity generative models from few examples.
Proceedings of the Thirty-Fourth Conference on Uncertainty in Artificial Intelligence, 2018

Towards Robust Interpretability with Self-Explaining Neural Networks.
Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018

Junction Tree Variational Autoencoder for Molecular Graph Generation.
Proceedings of the 35th International Conference on Machine Learning, 2018

Gromov-Wasserstein Alignment of Word Embedding Spaces.
Proceedings of the 2018 Conference on Empirical Methods in Natural Language Processing, Brussels, Belgium, October 31, 2018

Structured Optimal Transport.
Proceedings of the International Conference on Artificial Intelligence and Statistics, 2018

2017
Aspect-augmented Adversarial Networks for Domain Adaptation.
Trans. Assoc. Comput. Linguistics, 2017

Deep Transfer in Reinforcement Learning by Language Grounding.
CoRR, 2017

Style Transfer from Non-Parallel Text by Cross-Alignment.
Proceedings of the Advances in Neural Information Processing Systems 30: Annual Conference on Neural Information Processing Systems 2017, 2017

Predicting Organic Reaction Outcomes with Weisfeiler-Lehman Network.
Proceedings of the Advances in Neural Information Processing Systems 30: Annual Conference on Neural Information Processing Systems 2017, 2017

Local Aggregative Games.
Proceedings of the Advances in Neural Information Processing Systems 30: Annual Conference on Neural Information Processing Systems 2017, 2017

Learning Sleep Stages from Radio Signals: A Conditional Adversarial Architecture.
Proceedings of the 34th International Conference on Machine Learning, 2017

Sequence to Better Sequence: Continuous Revision of Combinatorial Structures.
Proceedings of the 34th International Conference on Machine Learning, 2017

Deriving Neural Architectures from Sequence and Graph Kernels.
Proceedings of the 34th International Conference on Machine Learning, 2017

Tree-structured decoding with doubly-recurrent neural networks.
Proceedings of the 5th International Conference on Learning Representations, 2017

A causal framework for explaining the predictions of black-box sequence-to-sequence models.
Proceedings of the 2017 Conference on Empirical Methods in Natural Language Processing, 2017

Learning Optimal Interventions.
Proceedings of the 20th International Conference on Artificial Intelligence and Statistics, 2017

2016
Word Embeddings as Metric Recovery in Semantic Spaces.
Trans. Assoc. Comput. Linguistics, 2016

Structured Prediction: From Gaussian Perturbations to Linear-Time Principled Algorithms.
Proceedings of the Thirty-Second Conference on Uncertainty in Artificial Intelligence, 2016

Learning Tree Structured Potential Games.
Proceedings of the Advances in Neural Information Processing Systems 29: Annual Conference on Neural Information Processing Systems 2016, 2016

Ten Pairs to Tag - Multilingual POS Tagging via Coarse Mapping between Embeddings.
Proceedings of the NAACL HLT 2016, 2016

Semi-supervised Question Retrieval with Gated Convolutions.
Proceedings of the NAACL HLT 2016, 2016

Learning Population-Level Diffusions with Generative RNNs.
Proceedings of the 33nd International Conference on Machine Learning, 2016

Rationalizing Neural Predictions.
Proceedings of the 2016 Conference on Empirical Methods in Natural Language Processing, 2016

Learning to refine text based recommendations.
Proceedings of the 2016 Conference on Empirical Methods in Natural Language Processing, 2016

CRAFT: ClusteR-specific Assorted Feature selecTion.
Proceedings of the 19th International Conference on Artificial Intelligence and Statistics, 2016

2015
An Unsupervised Method for Uncovering Morphological Chains.
Trans. Assoc. Comput. Linguistics, 2015

Denoising Bodies to Titles: Retrieving Similar Questions with Recurrent Convolutional Models.
CoRR, 2015

Steps Toward Deep Kernel Methods from Infinite Neural Networks.
CoRR, 2015

Word, graph and manifold embedding from Markov processes.
CoRR, 2015

Statistical Learning under Nonstationary Mixing Processes.
CoRR, 2015

Principal Differences Analysis: Interpretable Characterization of Differences between Distributions.
Proceedings of the Advances in Neural Information Processing Systems 28: Annual Conference on Neural Information Processing Systems 2015, 2015

From random walks to distances on unweighted graphs.
Proceedings of the Advances in Neural Information Processing Systems 28: Annual Conference on Neural Information Processing Systems 2015, 2015

Molding CNNs for text: non-linear, non-consecutive convolutions.
Proceedings of the 2015 Conference on Empirical Methods in Natural Language Processing, 2015

Metric recovery from directed unweighted graphs.
Proceedings of the Eighteenth International Conference on Artificial Intelligence and Statistics, 2015

2014
Controlling privacy in recommender systems.
Proceedings of the Advances in Neural Information Processing Systems 27: Annual Conference on Neural Information Processing Systems 2014, 2014

On Measure Concentration of Random Maximum A-Posteriori Perturbations.
Proceedings of the 31th International Conference on Machine Learning, 2014

A Unified Framework for Consistency of Regularized Loss Minimizers.
Proceedings of the 31th International Conference on Machine Learning, 2014

Greed is Good if Randomized: New Inference for Dependency Parsing.
Proceedings of the 2014 Conference on Empirical Methods in Natural Language Processing, 2014

Active Boundary Annotation using Random MAP Perturbations.
Proceedings of the Seventeenth International Conference on Artificial Intelligence and Statistics, 2014

Tight Bounds for the Expected Risk of Linear Classifiers and PAC-Bayes Finite-Sample Guarantees.
Proceedings of the Seventeenth International Conference on Artificial Intelligence and Statistics, 2014

Learning with Maximum A-Posteriori Perturbation Models.
Proceedings of the Seventeenth International Conference on Artificial Intelligence and Statistics, 2014

Steps to Excellence: Simple Inference with Refined Scoring of Dependency Trees.
Proceedings of the 52nd Annual Meeting of the Association for Computational Linguistics, 2014

Low-Rank Tensors for Scoring Dependency Structures.
Proceedings of the 52nd Annual Meeting of the Association for Computational Linguistics, 2014

2013
Inverse Covariance Estimation for High-Dimensional Data in Linear Time and Space: Spectral Methods for Riccati and Sparse Models.
Proceedings of the Twenty-Ninth Conference on Uncertainty in Artificial Intelligence, 2013

Learning Efficient Random Maximum A-Posteriori Predictors with Non-Decomposable Loss Functions.
Proceedings of the Advances in Neural Information Processing Systems 26: 27th Annual Conference on Neural Information Processing Systems 2013. Proceedings of a meeting held December 5-8, 2013

On Sampling from the Gibbs Distribution with Random Maximum A-Posteriori Perturbations.
Proceedings of the Advances in Neural Information Processing Systems 26: 27th Annual Conference on Neural Information Processing Systems 2013. Proceedings of a meeting held December 5-8, 2013

Two-Sided Exponential Concentration Bounds for Bayes Error Rate and Shannon Entropy.
Proceedings of the 30th International Conference on Machine Learning, 2013

2012
Primal-Dual methods for sparse constrained matrix completion.
Proceedings of the Fifteenth International Conference on Artificial Intelligence and Statistics, 2012

Approximate Inference in Additive Factorial HMMs with Application to Energy Disaggregation.
Proceedings of the Fifteenth International Conference on Artificial Intelligence and Statistics, 2012

Special Issue on the Fifth European Workshop on Probabilistic Graphical Models (PGM-2010).
Int. J. Approx. Reason., 2012

Proceedings of the Twenty-First Conference on Uncertainty in Artificial Intelligence (2005)
CoRR, 2012

Lineage-based identification of cellular states and expression programs.
Bioinform., 2012

Convergence Rate Analysis of MAP Coordinate Minimization Algorithms.
Proceedings of the Advances in Neural Information Processing Systems 25: 26th Annual Conference on Neural Information Processing Systems 2012. Proceedings of a meeting held December 3-6, 2012

On the Partition Function and Random Maximum A-Posteriori Perturbations.
Proceedings of the 29th International Conference on Machine Learning, 2012

2010
Learning Bayesian Network Structure using LP Relaxations.
Proceedings of the Thirteenth International Conference on Artificial Intelligence and Statistics, 2010

Discovering homotypic binding events at high spatial resolution.
Bioinform., 2010

More data means less inference: A pseudo-max approach to structured learning.
Proceedings of the Advances in Neural Information Processing Systems 23: 24th Annual Conference on Neural Information Processing Systems 2010. Proceedings of a meeting held 6-9 December 2010, 2010

Learning Efficiently with Approximate Inference via Dual Losses.
Proceedings of the 27th International Conference on Machine Learning (ICML-10), 2010

On Dual Decomposition and Linear Programming Relaxations for Natural Language Processing.
Proceedings of the 2010 Conference on Empirical Methods in Natural Language Processing, 2010

Dual Decomposition for Parsing with Non-Projective Head Automata.
Proceedings of the 2010 Conference on Empirical Methods in Natural Language Processing, 2010

Collaborative future event recommendation.
Proceedings of the 19th ACM Conference on Information and Knowledge Management, 2010

2009
Tree Block Coordinate Descent for MAP in Graphical Models.
Proceedings of the Twelfth International Conference on Artificial Intelligence and Statistics, 2009

2008
Tightening LP Relaxations for MAP using Message Passing.
Proceedings of the UAI 2008, 2008

Clusters and Coarse Partitions in LP Relaxations.
Proceedings of the Advances in Neural Information Processing Systems 21, 2008

2007
Automated Discovery of Functional Generality of Human Gene Expression Programs.
PLoS Comput. Biol., 2007

Predictive Discretization during Model Selection.
Proceedings of the Eleventh International Conference on Artificial Intelligence and Statistics, 2007

Approximate inference using conditional entropy decompositions.
Proceedings of the Eleventh International Conference on Artificial Intelligence and Statistics, 2007

Convergent Propagation Algorithms via Oriented Trees.
Proceedings of the UAI 2007, 2007

New Outer Bounds on the Marginal Polytope.
Proceedings of the Advances in Neural Information Processing Systems 20, 2007

Fixing Max-Product: Convergent Message Passing Algorithms for MAP LP-Relaxations.
Proceedings of the Advances in Neural Information Processing Systems 20, 2007

2006
Tractable Bayesian learning of tree belief networks.
Stat. Comput., 2006

Modeling the Combinatorial Functions of Multiple Transcription Factors.
J. Comput. Biol., 2006

Parameter Expanded Variational Bayesian Methods.
Proceedings of the Advances in Neural Information Processing Systems 19, 2006

Game Theoretic Algorithms for Protein-DNA binding.
Proceedings of the Advances in Neural Information Processing Systems 19, 2006

Approximate inference using planar graph decomposition.
Proceedings of the Advances in Neural Information Processing Systems 19, 2006

Semi-supervised analysis of gene expression profiles for lineage-specific development in the <i>Caenorhabditis elegans</i> embryo.
Proceedings of the Proceedings 14th International Conference on Intelligent Systems for Molecular Biology 2006, 2006

Data-Dependent Regularization.
Proceedings of the Semi-Supervised Learning, 2006

2005
MAP estimation via agreement on trees: message-passing and linear programming.
IEEE Trans. Inf. Theory, 2005

A new class of upper bounds on the log partition function.
IEEE Trans. Inf. Theory, 2005

Time Series Analysis of Gene Expression and Location Data.
Int. J. Artif. Intell. Tools, 2005

MAP estimation via agreement on (hyper)trees: Message-passing and linear programming
CoRR, 2005

Using term informativeness for named entity detection.
Proceedings of the SIGIR 2005: Proceedings of the 28th Annual International ACM SIGIR Conference on Research and Development in Information Retrieval, 2005

Focused Inference.
Proceedings of the Tenth International Workshop on Artificial Intelligence and Statistics, 2005

2004
Tree consistency and bounds on the performance of the max-product algorithm and its generalizations.
Stat. Comput., 2004

Physical Network Models.
J. Comput. Biol., 2004

Maximum-Margin Matrix Factorization.
Proceedings of the Advances in Neural Information Processing Systems 17 [Neural Information Processing Systems, 2004

Generalization Error Bounds for Collaborative Prediction with Low-Rank Matrices.
Proceedings of the Advances in Neural Information Processing Systems 17 [Neural Information Processing Systems, 2004

Distributed Information Regularization on Graphs.
Proceedings of the Advances in Neural Information Processing Systems 17 [Neural Information Processing Systems, 2004

Analysis of Signaling Pathways in Human T-Cells Using Bayesian Network Modeling of Single Cell Data.
Proceedings of the 3rd International IEEE Computer Society Computational Systems Bioinformatics Conference, 2004

2003
Tree-based reparameterization framework for analysis of sum-product and related algorithms.
IEEE Trans. Inf. Theory, 2003

Continuous Representations of Time-Series Gene Expression Data.
J. Comput. Biol., 2003

K-ary Clustering with Optimal Leaf Ordering for Gene Expression Data.
Bioinform., 2003

On Information Regularization.
Proceedings of the UAI '03, 2003

Physical network models and multi-source data integration.
Proceedings of the Sventh Annual International Conference on Computational Biology, 2003

Bias-Corrected Bootstrap and Model Uncertainty.
Proceedings of the Advances in Neural Information Processing Systems 16 [Neural Information Processing Systems, 2003

Linear Dependent Dimensionality Reduction.
Proceedings of the Advances in Neural Information Processing Systems 16 [Neural Information Processing Systems, 2003

Online Learning of Non-stationary Sequences.
Proceedings of the Advances in Neural Information Processing Systems 16 [Neural Information Processing Systems, 2003

Weighted Low-Rank Approximations.
Proceedings of the Machine Learning, 2003

Tree-reweighted belief propagation algorithms and approximate ML estimation by pseudo-moment matching.
Proceedings of the Ninth International Workshop on Artificial Intelligence and Statistics, 2003

2002
Bayesian Methods for Elucidating Genetic Regulatory Networks.
IEEE Intell. Syst., 2002

Unsupervised Active Learning in Large Domains.
Proceedings of the UAI '02, 2002

Continuation Methods for Mixing Heterogenous Sources.
Proceedings of the UAI '02, 2002

A new approach to analyzing gene expression time series data.
Proceedings of the Sixth Annual International Conference on Computational Biology, 2002

Combining Location and Expression Data for Principled Discovery of Genetic Regulatory Network Models.
Proceedings of the 7th Pacific Symposium on Biocomputing, 2002

Exact MAP Estimates by (Hyper)tree Agreement.
Proceedings of the Advances in Neural Information Processing Systems 15 [Neural Information Processing Systems, 2002

Information Regularization with Partially Labeled Data.
Proceedings of the Advances in Neural Information Processing Systems 15 [Neural Information Processing Systems, 2002

On the Dirichlet Prior and Bayesian Regularization.
Proceedings of the Advances in Neural Information Processing Systems 15 [Neural Information Processing Systems, 2002

2001
Using Graphical Models and Genomic Expression Data to Statistically Validate Models of Genetic Regulatory Networks.
Proceedings of the 6th Pacific Symposium on Biocomputing, 2001

Tree-based reparameterization for approximate inference on loopy graphs.
Proceedings of the Advances in Neural Information Processing Systems 14 [Neural Information Processing Systems: Natural and Synthetic, 2001

Partially labeled classification with Markov random walks.
Proceedings of the Advances in Neural Information Processing Systems 14 [Neural Information Processing Systems: Natural and Synthetic, 2001

Active Information Retrieval.
Proceedings of the Advances in Neural Information Processing Systems 14 [Neural Information Processing Systems: Natural and Synthetic, 2001

Fast optimal leaf ordering for hierarchical clustering.
Proceedings of the Ninth International Conference on Intelligent Systems for Molecular Biology, 2001

2000
Bayesian parameter estimation via variational methods.
Stat. Comput., 2000

Convergence Results for Single-Step On-Policy Reinforcement-Learning Algorithms.
Mach. Learn., 2000

A Discriminative Framework for Detecting Remote Protein Homologies.
J. Comput. Biol., 2000

Feature Selection and Dualities in Maximum Entropy Discrimination.
Proceedings of the UAI '00: Proceedings of the 16th Conference in Uncertainty in Artificial Intelligence, Stanford University, Stanford, California, USA, June 30, 2000

Kernel Expansions with Unlabeled Examples.
Proceedings of the Advances in Neural Information Processing Systems 13, 2000

Sequentially Fitting "Inclusive" Trees for Inference in Noisy-OR Networks.
Proceedings of the Advances in Neural Information Processing Systems 13, 2000

1999
An Introduction to Variational Methods for Graphical Models.
Mach. Learn., 1999

Variational Probabilistic Inference and the QMR-DT Network.
J. Artif. Intell. Res., 1999

Maximum Entropy Discrimination.
Proceedings of the Advances in Neural Information Processing Systems 12, [NIPS Conference, Denver, Colorado, USA, November 29, 1999

Using the Fisher Kernel Method to Detect Remote Protein Homologies.
Proceedings of the Seventh International Conference on Intelligent Systems for Molecular Biology, 1999

Probabilistic kernel regression models.
Proceedings of the Seventh International Workshop on Artificial Intelligence and Statistics, 1999

1998
Exploiting Generative Models in Discriminative Classifiers.
Proceedings of the Advances in Neural Information Processing Systems 11, [NIPS Conference, Denver, Colorado, USA, November 30, 1998

An Introduction to Variational Methods for Graphical Models.
Proceedings of the Learning in Graphical Models, 1998

Improving the Mean Field Approximation Via the Use of Mixture Distributions.
Proceedings of the Learning in Graphical Models, 1998

1997
Approximating Posterior Distributions in Belief Networks Using Mixtures.
Proceedings of the Advances in Neural Information Processing Systems 10, 1997

1996
Mean Field Theory for Sigmoid Belief Networks.
J. Artif. Intell. Res., 1996

Computing upper and lower bounds on likelihoods in intractable networks.
Proceedings of the UAI '96: Proceedings of the Twelfth Annual Conference on Uncertainty in Artificial Intelligence, 1996

Recursive Algorithms for Approximating Probabilities in Graphical Models.
Proceedings of the Advances in Neural Information Processing Systems 9, 1996

1995
Fast Learning by Bounding Likelihoods in Sigmoid Type Belief Networks.
Proceedings of the Advances in Neural Information Processing Systems 8, 1995

1994
On the Convergence of Stochastic Iterative Dynamic Programming Algorithms.
Neural Comput., 1994

Reinforcement Learning with Soft State Aggregation.
Proceedings of the Advances in Neural Information Processing Systems 7, 1994

Reinforcement Learning Algorithm for Partially Observable Markov Decision Problems.
Proceedings of the Advances in Neural Information Processing Systems 7, 1994

Learning Without State-Estimation in Partially Observable Markovian Decision Processes.
Proceedings of the Machine Learning, 1994


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