Search Results - "Steck, Harald"

Tumor Volume Combined With Number of Positive Lymph Node Stations Is a More Important Prognostic Factor Than TNM Stage for Survival of Non–Small-Cell Lung Cancer Patients Treated With (Chemo)radiotherapy by Dehing-Oberije, Cary, M.Sc, De Ruysscher, Dirk, M.D., Ph.D, van der Weide, Hiska, M.D, Hochstenbag, Monique, M.D., Ph.D, Bootsma, Gerben, M.D., Ph.D, Geraedts, Wiel, M.D, Pitz, Cordula, M.D., Ph.D, Simons, Jean, M.D., Ph.D, Teule, Jaap, M.D., Ph.D, Rahmy, Ali, M.D, Thimister, Paul, M.D., Ph.D, Steck, Harald, Ph.D, Lambin, Philippe, M.D., Ph.D

“…Purpose The current tumor, node, metastasis system needs refinement to improve its ability to predict survival of patients with non–small-cell lung cancer…”
Get full text

A simple but highly effective approach to evaluate the prognostic performance of gene expression signatures by Starmans, Maud H W, Fung, Glenn, Steck, Harald, Wouters, Bradly G, Lambin, Philippe

“…Highly parallel analysis of gene expression has recently been used to identify gene sets or 'signatures' to improve patient diagnosis and risk stratification…”
Get full text

A survey of collaborative filtering based social recommender systems by Yang, Xiwang, Guo, Yang, Liu, Yong, Steck, Harald

“…Recommendation plays an increasingly important role in our daily lives. Recommender systems automatically suggest to a user items that might be of interest to…”
Get full text

Probability kernel regression for WiFi localisation by Mirowski, Piotr, Whiting, Philip, Steck, Harald, Palaniappan, Ravishankar, MacDonald, Michael, Hartmann, Detlef, Ho, Tin Kam

“…Various methods have been developed for indoor localisation using WLAN signals. Algorithms that fingerprint the received signal strength indicators (RSSI) of…”
Get full text

Markov Random Fields for Collaborative Filtering by Steck, Harald

“…33rd Conference on Neural Information Processing Systems (NeurIPS 2019), Vancouver, Canada In this paper, we model the dependencies among the items that are…”
Get full text

Embarrassingly Shallow Autoencoders for Sparse Data by Steck, Harald

“…Combining simple elements from the literature, we define a linear model that is geared toward sparse data, in particular implicit feedback data for recommender…”
Get full text

Collaborative Filtering via High-Dimensional Regression by Steck, Harald

“…While the SLIM approach obtained high ranking-accuracy in many experiments in the literature, it is also known for its high computational cost of learning its…”
Get full text

Is Cosine-Similarity of Embeddings Really About Similarity? by Steck, Harald, Ekanadham, Chaitanya, Kallus, Nathan

“…ACM Web Conference 2024 (WWW 2024 Companion) Cosine-similarity is the cosine of the angle between two vectors, or equivalently the dot product between their…”
Get full text

On the Regularization of Autoencoders by Steck, Harald, Garcia, Dario Garcia

“…While much work has been devoted to understanding the implicit (and explicit) regularization of deep nonlinear networks in the supervised setting, this paper…”
Get full text

KL-divergence kernel regression for non-Gaussian fingerprint based localization by Mirowski, P., Steck, H., Whiting, P., Palaniappan, R., MacDonald, M., Tin Kam Ho

“…Various methods have been developed for indoor localization using WLAN signals. Algorithms that fingerprint the Received Signal Strength Indication (RSSI) of…”
Get full text

Public space behavior modeling with video and sensor analytics by Ho, Tin Kam, Matthews, Kim, O'Gorman, Lawrence, Steck, Harald

“…We present a review of technologies relevant to public space surveillance and describe a pilot study to explore the challenges. The general purpose of this…”
Get full text

Reindex-Then-Adapt: Improving Large Language Models for Conversational Recommendation by He, Zhankui, Xie, Zhouhang, Steck, Harald, Liang, Dawen, Jha, Rahul, Kallus, Nathan, McAuley, Julian

“…Large language models (LLMs) are revolutionizing conversational recommender systems by adeptly indexing item content, understanding complex conversational…”
Get full text

On the Use of Skeletons when Learning in Bayesian Networks by Steck, Harald

“…In this paper, we present a heuristic operator which aims at simultaneously optimizing the orientations of all the edges in an intermediate Bayesian network…”
Get full text

Ranking by Dependence - A Fair Criteria by Steck, Harald

“…Estimating the dependences between random variables, and ranking them accordingly, is a prevalent problem in machine learning. Pursuing frequentist and…”
Get full text

Learning the Bayesian Network Structure: Dirichlet Prior versus Data by Steck, Harald

“…In the Bayesian approach to structure learning of graphical models, the equivalent sample size (ESS) in the Dirichlet prior over the model parameters was…”
Get full text

Large Language Models as Zero-Shot Conversational Recommenders by He, Zhankui, Xie, Zhouhang, Jha, Rahul, Steck, Harald, Liang, Dawen, Feng, Yesu, Majumder, Bodhisattwa Prasad, Kallus, Nathan, McAuley, Julian

“…In this paper, we present empirical studies on conversational recommendation tasks using representative large language models in a zero-shot setting with three…”
Get full text

Unsupervised Active Learning in Large Domains by Steck, Harald, Jaakkola, Tommi S

“…Active learning is a powerful approach to analyzing data effectively. We show that the feasibility of active learning depends crucially on the choice of…”
Get full text